The 500 largest companies in the USA Data Analysis¶

In [24]:
# import libraries 

import requests # open web connection
import time
import datetime

# Connect to Website and pull in data
URL = 'https://www.50pros.com/fortune500'
# URL = 'http://localhost:9088'

# Set the headers for the Web Browser. 
# You can get it from 'https://httpbin.org/get' and take a look at 'User-Agent' element.
headers = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.108 Safari/537.36", "Accept-Encoding":"gzip, deflate", "Accept":"text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8", "DNT":"1","Connection":"close", "Upgrade-Insecure-Requests":"1"}

# Open web connection to the website
page = requests.get(URL, headers=headers)
print(page)
<Response [200]>
In [ ]:
# Scrap the Web content for table
import pandas as pd
pd.set_option('display.max_rows', None)

df = pd.read_html(URL)
df[0]
In [25]:
# Save the scraped content into CSV file
# df.to_csv(r'C:\PAULDATA\Paulus_Data_Analyst\Portfolio_Projects\The_500_Largest_Companies_in_USA\Largest_500_Companies.csv', index = False)
In [1]:
##### Read 500 Largest Companies from stored CSV file

# Import all needed modules
import pandas as pd
import geopandas as gpd # pip install geopandas if it's not installed yet
import matplotlib.pyplot as plt
import mapclassify # pip install mapclassify if not yet installed
import folium

# Set to display all columns
pd.set_option('display.max_columns',None)
pd.set_option('display.max_rows',None)
pd.options.display.float_format = '{:,.0f}'.format
plt.rcParams['figure.figsize'] = (12, 8)

# Read the Dataframe from the CSV file
df = pd.read_csv(r'C:\PAULDATA\Paulus_Data_Analyst\Portfolio_Projects\The_500_Largest_Companies_in_USA\Largest_500_Companies.csv')
In [2]:
##### Data Cleaning
# Remove Duplicate data from raw table
df = df.drop_duplicates()

# Drop/remove all entries with blanks
# df.dropna(subset='temperature_2m', inplace=True)
# df.dropna(subset='relative_humidity_2m', inplace=True)
df.dropna(inplace=True)
df

# Check whether there's still any blank rows/columns
df[df.isna().any(axis=1)]
Out[2]:
Rank Company Industry City State Zip Code Website Employees Revenue (rounded) CEO
In [3]:
# Remove $ sign from Column 'Revenue (rounded)'
df['Revenue (rounded)'] = df['Revenue (rounded)'].str.replace('$','')
df['Revenue (rounded)'] = df['Revenue (rounded)'].str.replace(',','')

df['Employees'] = df['Employees'].str.replace(',','')

# Convert the type of Column 'Revenue (rounded)' into Float type
df['Revenue (rounded)'] = df['Revenue (rounded)'].astype(float)

# Convert the type of Column 'Employees' into Int type
df['Employees'] = df['Employees'].astype(int)

# Convert the type of Column 'Zip Code' into String type
df['Zip Code'] = df['Zip Code'].astype(str)
df['Zip Code'] = df['Zip Code'].str.zfill(5)

# Drop Column 'Rank' coz we don't need it
df.drop('Rank', axis=1, inplace=True)
In [4]:
df.head(2).style.format({'Employees': '{:,.0f}', 'Revenue (rounded)': '{:,.2f}'})
Out[4]:
  Company Industry City State Zip Code Website Employees Revenue (rounded) CEO
0 Walmart General Merchandisers Bentonville Arkansas 72712 walmart.com 2,100,000 681,000,000,000.00 Douglas McMillon
1 Amazon Internet Services and Retailing Seattle Washington 98109 amazon.com 1,556,000 638,000,000,000.00 Andrew Jassy
In [5]:
# Check whether there's still ZipCodes that less than 5 in length.
for index, row in df.iterrows():
    if len(row['Zip Code']) < 5:
        print("Ada yang panjangnya kurang dari 5")

# To mark that the For loop has finished.
print("Finished")
Finished
In [6]:
# Map of States in USA
gdfsts = gpd.read_file(r"C:\PAULDATA\Paulus_Data_Analyst\Portfolio_Projects\110m_cultural\ne_110m_admin_1_states_provinces.shp")
gdfsts = gdfsts.query("name != 'Hawaii'")
gdfsts = gdfsts.query("name != 'Alaska'")
gdfsts = gdfsts.rename(columns={'name': 'State'})
gdfsts = gdfsts[['State','region','postal','latitude','longitude','geometry']]
In [7]:
gdfsts.explore(column='State', cmap='hsv', edgecolor = 'black', legend=False)
Out[7]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [8]:
# Draw the States Map of Fortune500 Companies
gdfsts500 = gdfsts.merge(df, how = 'inner', on = ['State'])
gdfsts500.explore(column='State', cmap='hsv', edgecolor='black', legend=False)
Out[8]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [9]:
# Sneak peek at GeoDataframe of Fortune500 Companies
gdfsts500.head(2)
Out[9]:
State region postal latitude longitude geometry Company Industry City Zip Code Website Employees Revenue (rounded) CEO
0 Minnesota Midwest MN 46 -93 POLYGON ((-89.95766 47.28691, -90.13175 47.292... UnitedHealth Health Care: Insurance and Managed Care Eden Prairie 55344 unitedhealthgroup.com 400000 400,300,000,000 Stephen Hemsley
1 Minnesota Midwest MN 46 -93 POLYGON ((-89.95766 47.28691, -90.13175 47.292... Target General Merchandisers Minneapolis 55403 target.com 440000 106,600,000,000 Brian Cornell

Draw the Map of Cities in Fortune500 Dataset¶

In [10]:
dfusact = pd.read_excel(r'C:\PAULDATA\Paulus_Data_Analyst\Portfolio_Projects\simplemaps_uszips_basicv1.91\uszips.xlsx', sheet_name='ZIP2')

# Convert the type of Column 'Zip Code' into String type
#dfusact['Zip Code'] = dfusact['Zip Code'].astype(int)
dfusact['Zip Code'] = dfusact['Zip Code'].astype(str)
dfusact['Zip Code'] = dfusact['Zip Code'].str.replace('.0','')
dfusact['Zip Code'] = dfusact['Zip Code'].str.zfill(5)
dfusact.head(2)
Out[10]:
Zip Code Latitude Longitude Population
0 00601 18 -67 16,721
1 00602 18 -67 37,510
In [11]:
# Check Data Types of Geo location data
In [12]:
type(dfusact['Latitude'][0])
Out[12]:
numpy.float64
In [13]:
type(dfusact['Longitude'][0])
Out[13]:
numpy.float64
In [14]:
type(dfusact['Zip Code'][0])
Out[14]:
str
In [15]:
# Create geometry column
geometry = gpd.points_from_xy(dfusact['Longitude'], dfusact['Latitude'], crs="EPSG:4326")

# Create GeoDataFrame
gdfusact = gpd.GeoDataFrame(dfusact, geometry=geometry)
In [16]:
# Check the data type of 'geometry' Column
type(gdfusact['geometry'])
Out[16]:
geopandas.geoseries.GeoSeries
In [17]:
# Create Geodataframe of the Fortune500 cities with joining 'df' Dataframe with 'gdfusact' Dataframe
#gdfusact500 = gdfusact.merge(df, how = 'inner', on = ['City','State'])
gdfusact500 = gdfusact.merge(df, how = 'inner', on = ['Zip Code'])

# Let's explore one of the City in Fortune500 list
gdfusact500.where(gdfusact500['Zip Code'] == '44143').dropna().style.format({'Employees': '{:,.0f}', 'Revenue (rounded)': '{:,.2f}'})
Out[17]:
  Zip Code Latitude Longitude Population geometry Company Industry City State Website Employees Revenue (rounded) CEO
218 44143 41.553580 -81.475130 24337.000000 POINT (-81.47513 41.55358) Progressive Insurance: Property and Casualty (Stock) Mayfield Village Ohio progressive.com 66,300 75,400,000,000.00 Susan Patricia Griffith
In [18]:
# How Mayfield Village looks like
gdfusact500.query("City == 'Mayfield Village'").explore()
Out[18]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [19]:
# US Fortune500 Companies Map (2025) color mapped by Population Column.
gdfusact500.explore(column='Population', name='Cities in Fortune500',cmap='RdYlGn')
Out[19]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [20]:
# Conclusion: Fortune500 Companies are mostly located on Eastern half of mainland USA.
In [ ]:

In [21]:
gdf2 = gpd.read_file(r"C:\PAULDATA\Paulus_Data_Analyst\Portfolio_Projects\nyc-zip-code-tabulation-areas-polygons.geojson")
gdf2
Out[21]:
OBJECTID postalCode PO_NAME STATE borough ST_FIPS CTY_FIPS BLDGpostalCode Shape_Leng Shape_Area @id geometry
0 1 11372 Jackson Heights NY Queens 36 081 0 20,625 20,163,284 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.86942 40.74916, -73.89507 40.746...
1 2 11004 Glen Oaks NY Queens 36 081 0 23,003 22,606,527 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.71068 40.75004, -73.70869 40.748...
2 3 11040 New Hyde Park NY Queens 36 081 0 15,749 6,269,333 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.70098 40.7389, -73.70309 40.7445...
3 4 11426 Bellerose NY Queens 36 081 0 35,933 49,418,364 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.7227 40.75373, -73.72251 40.7533...
4 5 11365 Fresh Meadows NY Queens 36 081 0 38,694 69,385,866 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.81089 40.72717, -73.81116 40.728...
5 6 11373 Elmhurst NY Queens 36 081 0 33,756 42,659,400 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.88722 40.72753, -73.88723 40.728...
6 7 11001 Floral Park NY Queens 36 081 0 13,595 9,155,180 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.70098 40.7389, -73.6996 40.73959...
7 8 11375 Forest Hills NY Queens 36 081 0 36,277 55,587,772 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.85625 40.73672, -73.85205 40.737...
8 9 11427 Queens Village NY Queens 36 081 0 31,232 39,568,339 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.74169 40.73682, -73.73568 40.738...
9 10 11374 Rego Park NY Queens 36 081 0 26,324 25,203,459 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.86451 40.73407, -73.85872 40.735...
10 11 11366 Fresh Meadows NY Queens 36 081 0 27,283 20,358,593 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.77011 40.73178, -73.7751 40.7308...
11 12 11423 Hollis NY Queens 36 081 0 31,340 45,095,032 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.77011 40.73178, -73.76536 40.725...
12 13 11428 Queens Village NY Queens 36 081 0 22,516 21,985,773 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.72775 40.72258, -73.72762 40.722...
13 14 11432 Jamaica NY Queens 36 081 0 33,124 60,177,576 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.80904 40.71991, -73.79288 40.725...
14 15 11379 Middle Village NY Queens 36 081 0 33,528 57,537,331 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.8719 40.72686, -73.87182 40.7267...
15 16 11429 Queens Village NY Queens 36 081 0 26,527 39,559,398 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.72848 40.72077, -73.72793 40.719...
16 17 11435 Jamaica NY Queens 36 081 0 34,404 42,105,899 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.82606 40.7154, -73.82306 40.7161...
17 18 11415 Kew Gardens NY Queens 36 081 0 21,075 16,802,280 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.82606 40.7154, -73.82348 40.7123...
18 19 11418 Richmond Hill NY Queens 36 081 0 31,854 32,025,131 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.83715 40.70796, -73.83655 40.708...
19 20 11433 Jamaica NY Queens 36 081 0 30,604 47,739,433 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.77968 40.7086, -73.77937 40.7078...
20 21 11451 Jamaica NY Queens 36 081 0 2,962 487,600 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.80157 40.70121, -73.79887 40.702...
21 22 11221 Brooklyn NY Brooklyn 36 047 0 30,948 38,580,480 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.93822 40.68389, -73.94389 40.683...
22 23 11421 Woodhaven NY Queens 36 081 0 22,224 24,314,442 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.8492 40.69827, -73.84741 40.6957...
23 24 11419 South Richmond Hill NY Queens 36 081 0 23,069 31,278,858 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.83754 40.69136, -73.82812 40.694...
24 25 11434 Jamaica NY Queens 36 081 0 43,830 87,379,704 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.76989 40.69631, -73.76605 40.692...
25 26 11216 Brooklyn NY Brooklyn 36 047 0 26,473 26,478,229 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.94564 40.69203, -73.94389 40.683...
26 27 11416 Ozone Park NY Queens 36 081 0 21,631 18,854,850 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.8443 40.68944, -73.83754 40.6913...
27 28 11233 Brooklyn NY Brooklyn 36 047 0 30,234 37,871,694 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.93822 40.68389, -73.91785 40.686...
28 29 11436 Jamaica NY Queens 36 081 0 20,579 22,699,295 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.80585 40.68291, -73.79391 40.686...
29 30 11213 Brooklyn NY Brooklyn 36 047 0 23,899 29,631,004 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.9374 40.67973, -73.92906 40.6792...
30 31 11212 Brooklyn NY Brooklyn 36 047 0 26,622 41,972,104 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.90294 40.67084, -73.90223 40.668...
31 32 11225 Brooklyn NY Brooklyn 36 047 0 23,346 23,698,630 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.95797 40.67066, -73.95505 40.670...
32 33 11218 Brooklyn NY Brooklyn 36 047 0 30,623 36,868,799 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97208 40.6506, -73.9714 40.64826...
33 34 11226 Brooklyn NY Brooklyn 36 047 0 28,636 39,408,598 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.9619 40.65487, -73.96152 40.6550...
34 35 11219 Brooklyn NY Brooklyn 36 047 0 29,464 42,002,738 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98906 40.64412, -73.99193 40.642...
35 36 11210 Brooklyn NY Brooklyn 36 047 0 29,975 47,887,023 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.9584 40.63633, -73.95374 40.6385...
36 37 11230 Brooklyn NY Brooklyn 36 047 0 31,795 49,926,703 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.96451 40.63669, -73.96422 40.635...
37 38 11204 Brooklyn NY Brooklyn 36 047 0 30,325 43,555,185 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98108 40.63529, -73.98085 40.635...
38 39 10471 Bronx NY Bronx 36 005 0 53,209 89,651,407 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.88192 40.90667, -73.8779 40.9055...
39 40 10470 Bronx NY Bronx 36 005 0 32,649 21,543,462 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.8779 40.90555, -73.87786 40.9059...
40 41 10466 Bronx NY Bronx 36 005 0 35,358 55,262,491 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.84464 40.90475, -73.84443 40.904...
41 42 10467 Bronx NY Bronx 36 005 0 43,945 69,336,166 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.88011 40.8952, -73.87459 40.8957...
42 43 10463 Bronx NY Bronx 36 005 0 47,485 36,703,382 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.92065 40.88724, -73.92038 40.887...
43 44 10475 Bronx NY Bronx 36 005 0 45,028 38,633,297 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.82722 40.89093, -73.82511 40.890...
44 45 10464 Bronx NY Bronx 36 005 0 95,376 76,257,485 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.81539 40.88939, -73.81365 40.888...
45 46 10469 Bronx NY Bronx 36 005 0 34,901 68,040,887 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.85588 40.88386, -73.85011 40.882...
46 47 10468 Bronx NY Bronx 36 005 0 37,083 34,447,605 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.88701 40.88247, -73.88592 40.880...
47 48 10463 Bronx NY Manhattan 36 061 0 7,792 3,119,702 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.91544 40.87559, -73.91509 40.876...
48 49 10458 Bronx NY Bronx 36 005 0 29,391 35,968,813 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.8848 40.87846, -73.88423 40.8787...
49 50 10034 New York NY Manhattan 36 061 0 28,234 24,503,892 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.92062 40.873, -73.92004 40.87328...
50 51 10033 New York NY Manhattan 36 061 0 29,416 16,156,054 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.93213 40.86945, -73.93128 40.868...
51 52 10462 Bronx NY Bronx 36 005 0 49,496 53,022,514 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.84218 40.83537, -73.83915 40.835...
52 53 10040 New York NY Manhattan 36 061 0 24,555 16,340,743 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.93379 40.86307, -73.93298 40.865...
53 54 10453 Bronx NY Bronx 36 005 0 26,399 25,748,509 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.89995 40.85742, -73.90134 40.855...
54 55 10465 Bronx NY Bronx 36 005 0 96,349 108,423,743 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.83915 40.83568, -73.83869 40.835...
55 56 10464 Bronx NY Bronx 36 005 0 14,922 4,512,531 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.772 40.85712, -73.77204 40.85894...
56 57 10464 Bronx NY Bronx 36 005 0 26,774 11,587,954 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.79235 40.85607, -73.79204 40.855...
57 58 10461 Bronx NY Bronx 36 005 0 35,943 62,824,058 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.84218 40.83537, -73.84543 40.834...
58 59 10457 Bronx NY Bronx 36 005 0 29,927 37,640,607 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.89995 40.85742, -73.89573 40.856...
59 60 10460 Bronx NY Bronx 36 005 0 41,386 35,155,667 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.87687 40.85539, -73.87732 40.854...
60 61 10032 New York NY Manhattan 36 061 0 31,658 23,159,566 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.94692 40.85053, -73.94258 40.849...
61 62 10452 Bronx NY Bronx 36 005 0 24,379 27,550,386 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.9281 40.84532, -73.92732 40.8464...
62 63 10456 Bronx NY Bronx 36 005 0 30,925 29,933,452 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.91314 40.83981, -73.91208 40.839...
63 64 10472 Bronx NY Bronx 36 005 0 27,006 30,963,245 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.88011 40.83723, -73.87747 40.836...
64 65 10031 New York NY Manhattan 36 061 0 23,228 16,902,152 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.94009 40.83035, -73.93968 40.829...
65 66 10039 New York NY Manhattan 36 061 0 15,005 8,419,028 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.9344 40.8361, -73.93492 40.83519...
66 67 10459 Bronx NY Bronx 36 005 0 24,994 22,551,941 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.8963 40.83354, -73.89477 40.8343...
67 68 10451 Bronx NY Bronx 36 005 0 32,574 28,944,107 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.93294 40.82772, -73.93311 40.828...
68 69 10473 Bronx NY Bronx 36 005 0 46,333 59,522,355 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.847 40.828, -73.8458 40.82832, -...
69 70 10030 New York NY Manhattan 36 061 0 11,274 7,757,661 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.93623 40.82044, -73.9418 40.8128...
70 71 10027 New York NY Manhattan 36 061 0 31,598 24,695,279 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.96569 40.80903, -73.96442 40.810...
71 72 10474 Bronx NY Bronx 36 005 0 30,197 40,614,090 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.89543 40.81584, -73.89332 40.817...
72 73 10455 Bronx NY Bronx 36 005 0 26,038 19,846,919 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.90337 40.81878, -73.9016 40.8196...
73 74 10037 New York NY Manhattan 36 061 0 12,512 7,188,981 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.93382 40.8195, -73.93381 40.8156...
74 75 10024 New York NY Manhattan 36 061 0 40,064 22,877,335 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.9659 40.80881, -73.96689 40.8077...
75 76 10454 Bronx NY Bronx 36 005 0 25,984 31,063,613 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.93176 40.80793, -73.93062 40.808...
76 77 10026 New York NY Manhattan 36 061 0 15,645 11,092,681 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.9446 40.80323, -73.94922 40.7969...
77 78 10035 New York NY Manhattan 36 061 0 17,087 15,445,657 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.93326 40.80724, -73.93129 40.805...
78 79 10025 New York NY Manhattan 36 061 0 20,734 19,631,044 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.95936 40.80612, -73.95983 40.805...
79 80 10035 New York NY Manhattan 36 061 0 25,010 23,494,871 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.92742 40.79839, -73.92694 40.799...
80 81 11357 Whitestone NY Queens 36 081 0 44,133 77,359,111 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.82482 40.79715, -73.82423 40.797...
81 82 10029 New York NY Manhattan 36 061 0 19,647 22,963,436 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.94646 40.80067, -73.93092 40.794...
82 83 00083 Central Park NY Manhattan 36 061 0 32,711 38,300,990 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.94922 40.79691, -73.97301 40.764...
83 84 11356 College Point NY Queens 36 081 0 39,906 43,321,159 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.85465 40.78943, -73.85447 40.790...
84 85 11359 Bayside NY Queens 36 081 0 12,842 6,567,982 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.78178 40.79485, -73.78323 40.794...
85 86 11360 Bayside NY Queens 36 081 0 31,491 38,834,824 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.78664 40.79032, -73.78389 40.790...
86 87 11105 Astoria NY Queens 36 081 0 36,788 48,795,608 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.89672 40.78294, -73.89618 40.783...
87 88 10128 New York NY Manhattan 36 061 0 15,005 11,011,682 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.94359 40.78283, -73.94388 40.781...
88 89 11371 Flushing NY Queens 36 081 0 33,739 30,558,475 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.8851 40.77846, -73.88525 40.7786...
89 90 10023 New York NY Manhattan 36 061 0 22,471 15,212,713 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.99307 40.77434, -73.98964 40.772...
90 91 11363 Little Neck NY Queens 36 081 0 27,323 24,242,790 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.75506 40.77646, -73.75483 40.776...
91 92 10028 New York NY Manhattan 36 061 0 18,177 9,842,046 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.95992 40.78221, -73.94663 40.776...
92 93 11354 Flushing NY Queens 36 081 0 44,429 61,985,147 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.84282 40.76615, -73.84287 40.765...
93 94 11102 Astoria NY Queens 36 081 0 21,057 19,116,258 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.92828 40.7769, -73.92398 40.7746...
94 95 11370 East Elmhurst NY Queens 36 081 0 28,831 23,600,231 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.89144 40.77636, -73.89145 40.776...
95 96 10021 New York NY Manhattan 36 061 0 14,364 10,495,133 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.94908 40.76828, -73.95232 40.764...
96 97 11361 Bayside NY Queens 36 081 0 33,141 50,163,518 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.76642 40.77595, -73.76574 40.774...
97 98 11358 Flushing NY Queens 36 081 0 31,560 54,622,541 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.80389 40.7749, -73.79276 40.7740...
98 99 11362 Little Neck NY Queens 36 081 0 34,988 54,680,551 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.75195 40.76336, -73.74749 40.764...
99 100 10044 New York NY Manhattan 36 061 0 21,449 6,296,113 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.96025 40.7516, -73.9593 40.75328...
100 101 11369 East Elmhurst NY Queens 36 081 0 25,542 30,060,493 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.88782 40.76721, -73.88589 40.767...
101 102 11103 Astoria NY Queens 36 081 0 21,849 20,222,395 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.91431 40.77152, -73.91167 40.769...
102 103 11106 Astoria NY Queens 36 081 0 22,169 23,866,113 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.93446 40.77118, -73.93421 40.771...
103 104 11368 Corona NY Queens 36 081 0 51,118 72,489,663 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.86264 40.76689, -73.86272 40.766...
104 105 11377 Woodside NY Queens 36 081 0 46,887 71,832,387 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.90203 40.76742, -73.89308 40.765...
105 106 10036 New York NY Manhattan 36 061 0 16,419 11,395,111 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98134 40.75865, -73.97812 40.757...
106 107 11355 Flushing NY Queens 36 081 0 33,070 49,383,079 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.83787 40.75448, -73.8338 40.7567...
107 108 11101 Long Island City NY Queens 36 081 0 55,297 79,311,463 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.92246 40.75743, -73.91467 40.753...
108 109 11364 Oakland Gardens NY Queens 36 081 0 37,489 84,259,665 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.77981 40.7519, -73.77618 40.7528...
109 110 10018 New York NY Manhattan 36 061 0 19,510 10,705,796 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.0017 40.76138, -73.99396 40.7582...
110 111 10020 New York NY Manhattan 36 061 0 3,612 697,297 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.9772 40.75854, -73.97812 40.7572...
111 112 11005 Floral Park NY Queens 36 081 0 15,261 9,075,527 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.71291 40.75995, -73.71239 40.759...
112 113 10017 New York NY Manhattan 36 061 0 14,309 9,794,383 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97765 40.75791, -73.9653 40.7526...
113 114 10001 New York NY Manhattan 36 061 0 19,254 17,794,941 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.00827 40.75259, -74.00763 40.754...
114 115 10011 New York NY Manhattan 36 061 0 24,714 18,118,417 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.99232 40.74357, -73.99416 40.741...
115 116 10016 New York NY Manhattan 36 061 0 18,193 15,042,403 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98182 40.7522, -73.97078 40.7475...
116 117 11104 Sunnyside NY Queens 36 081 0 21,699 12,084,432 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.90984 40.75162, -73.90944 40.750...
117 118 11109 Long Island City NY Queens 36 081 0 2,453 231,863 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.95946 40.74409, -73.95938 40.744...
118 119 10010 New York NY Manhattan 36 061 0 23,513 9,768,395 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98775 40.74407, -73.98453 40.742...
119 120 11367 Flushing NY Queens 36 081 0 33,506 72,810,152 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.83761 40.74324, -73.83516 40.743...
120 121 10014 New York NY Manhattan 36 061 0 20,454 14,151,052 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.00095 40.73171, -74.00214 40.729...
121 122 10003 New York NY Manhattan 36 061 0 17,396 15,538,376 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97986 40.73497, -73.98864 40.722...
122 123 11222 Brooklyn NY Brooklyn 36 047 0 32,221 42,904,554 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.96166 40.72587, -73.96109 40.729...
123 124 10002 New York NY Manhattan 36 061 0 36,484 26,280,129 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97442 40.73642, -73.9745 40.7356...
124 125 11378 Maspeth NY Queens 36 081 0 42,329 66,342,001 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.92421 40.73552, -73.92277 40.734...
125 126 10009 New York NY Manhattan 36 061 0 16,247 15,903,520 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97346 40.73071, -73.97249 40.729...
126 127 10012 New York NY Manhattan 36 061 0 12,423 9,193,739 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.99657 40.72955, -73.99155 40.727...
127 128 10013 New York NY Manhattan 36 061 0 19,248 15,580,578 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.00373 40.72625, -74.00457 40.724...
128 129 11211 Brooklyn NY Brooklyn 36 047 0 50,607 58,162,525 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.92919 40.72465, -73.92941 40.724...
129 130 10007 New York NY Manhattan 36 061 0 13,425 5,328,635 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.01362 40.71631, -74.01339 40.717...
130 131 11237 Brooklyn NY Brooklyn 36 047 0 30,773 27,373,778 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.92817 40.71421, -73.92409 40.713...
131 132 11385 Ridgewood NY Queens 36 081 0 67,619 125,023,075 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.92409 40.71396, -73.90031 40.712...
132 133 10038 New York NY Manhattan 36 061 0 12,605 7,022,761 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.99923 40.70787, -73.99979 40.707...
133 134 11206 Brooklyn NY Brooklyn 36 047 0 28,571 40,680,015 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.9348 40.71337, -73.93228 40.7077...
134 135 10006 New York NY Manhattan 36 061 0 6,795 1,716,641 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.01123 40.71037, -74.00999 40.709...
135 136 11412 Saint Albans NY Queens 36 081 0 29,899 46,687,804 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.75047 40.70564, -73.74528 40.694...
136 137 10005 New York NY Manhattan 36 061 0 6,384 2,082,901 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.00597 40.70432, -74.00777 40.703...
137 138 11251 Brooklyn NY Brooklyn 36 047 0 31,556 10,379,322 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97556 40.69952, -73.97537 40.699...
138 139 10004 New York NY Manhattan 36 061 0 13,770 4,001,782 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.00597 40.70432, -74.0058 40.7042...
139 140 11411 Cambria Heights NY Queens 36 081 0 27,775 35,889,597 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.72466 40.70581, -73.72465 40.687...
140 141 11201 Brooklyn NY Brooklyn 36 047 0 41,924 41,094,887 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.99804 40.69877, -74.00002 40.699...
141 142 10004 New York NY Manhattan 36 061 0 6,450 1,202,708 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.04166 40.69645, -74.04368 40.698...
142 143 11205 Brooklyn NY Brooklyn 36 047 0 22,054 23,159,721 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.95335 40.69934, -73.95132 40.689...
143 144 11208 Brooklyn NY Brooklyn 36 047 0 49,932 79,294,685 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.86632 40.68336, -73.86603 40.681...
144 145 11207 Brooklyn NY Brooklyn 36 047 0 48,842 73,742,269 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.90368 40.69046, -73.90211 40.692...
145 146 10004 New York NY Manhattan 36 061 0 12,620 7,679,616 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.02418 40.68392, -74.0253 40.6840...
146 147 10004 New York NY Manhattan 36 061 0 3,246 670,708 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.04699 40.69012, -74.04723 40.690...
147 148 11413 Springfield Gardens NY Queens 36 081 0 54,283 85,392,925 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.73365 40.68554, -73.73222 40.685...
148 149 11217 Brooklyn NY Brooklyn 36 047 0 22,011 21,648,158 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97313 40.68962, -73.97269 40.687...
149 150 11238 Brooklyn NY Brooklyn 36 047 0 26,935 29,429,423 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.95702 40.67329, -73.95797 40.670...
150 151 11231 Brooklyn NY Brooklyn 36 047 0 45,957 39,379,691 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98999 40.68332, -73.9913 40.6814...
151 152 11422 Rosedale NY Queens 36 081 0 55,579 60,091,179 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.72476 40.68743, -73.72461 40.687...
152 153 11420 South Ozone Park NY Queens 36 081 0 33,735 61,879,568 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.80795 40.68707, -73.80155 40.673...
153 154 11417 Ozone Park NY Queens 36 081 0 26,925 31,099,087 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.83427 40.68533, -73.83352 40.683...
154 155 11215 Brooklyn NY Brooklyn 36 047 0 37,187 61,922,822 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98853 40.67955, -73.97042 40.672...
155 156 11414 Howard Beach NY Queens 36 081 0 62,133 63,974,665 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.83339 40.66678, -73.83291 40.666...
156 157 11231 Brooklyn NY Brooklyn 36 047 0 5,642 701,979 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.01658 40.66476, -74.01726 40.665...
157 158 11232 Brooklyn NY Brooklyn 36 047 0 64,231 55,879,065 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.99841 40.67131, -73.99633 40.667...
158 159 11430 Jamaica NY Queens 36 081 0 103,039 199,913,664 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.78941 40.66684, -73.7896 40.6657...
159 160 11203 Brooklyn NY Brooklyn 36 047 0 32,800 60,644,835 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.9427 40.66406, -73.93716 40.6637...
160 161 11239 Brooklyn NY Brooklyn 36 047 0 36,129 41,794,661 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.86623 40.65876, -73.86599 40.658...
161 162 11236 Brooklyn NY Brooklyn 36 047 0 44,837 96,373,992 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.89888 40.65646, -73.89873 40.655...
162 163 11220 Brooklyn NY Brooklyn 36 047 0 39,989 47,453,786 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.02449 40.65092, -74.01867 40.647...
163 164 10301 Staten Island NY Staten Island 36 085 0 79,639 105,182,713 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.08931 40.64733, -74.08764 40.648...
164 165 10310 Staten Island NY Staten Island 36 085 0 43,886 53,463,275 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.12065 40.64104, -74.11961 40.641...
165 166 10303 Staten Island NY Staten Island 36 085 0 54,576 81,629,774 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.17843 40.64254, -74.1778 40.6426...
166 167 11234 Brooklyn NY Brooklyn 36 047 0 115,170 206,201,040 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.93439 40.63483, -73.93226 40.634...
167 168 10302 Staten Island NY Staten Island 36 085 0 27,433 29,555,323 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.13926 40.64074, -74.13902 40.640...
168 169 11693 Far Rockaway NY Queens 36 081 0 87,509 46,471,727 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.83205 40.63516, -73.83245 40.635...
169 170 11209 Brooklyn NY Brooklyn 36 047 0 37,123 57,842,314 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.03693 40.63873, -74.03596 40.638...
170 171 10304 Staten Island NY Staten Island 36 085 0 85,662 98,226,680 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.08412 40.63478, -74.08231 40.633...
171 172 10314 Staten Island NY Staten Island 36 085 0 126,072 473,985,727 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.11967 40.62174, -74.11913 40.620...
172 173 11693 Far Rockaway NY Brooklyn 36 047 0 9,480 3,497,516 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.84076 40.62536, -73.84306 40.627...
173 174 11228 Brooklyn NY Brooklyn 36 047 0 29,618 43,893,025 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.01634 40.63029, -74.01605 40.631...
174 175 11096 Inwood NY Queens 36 081 0 5,205 1,512,446 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.7674 40.61546, -73.76965 40.6156...
175 176 10305 Staten Island NY Staten Island 36 085 0 55,570 111,441,829 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.06361 40.61655, -74.06139 40.614...
176 177 11229 Brooklyn NY Brooklyn 36 047 0 43,382 60,119,326 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.94483 40.61605, -73.94457 40.614...
177 178 11214 Brooklyn NY Brooklyn 36 047 0 52,862 61,096,539 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98725 40.60724, -73.98255 40.582...
178 179 11691 Far Rockaway NY Queens 36 081 0 70,128 83,927,815 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.74691 40.61173, -73.74654 40.611...
179 180 11096 Inwood NY Queens 36 081 0 1,455 111,974 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.74906 40.61181, -73.74729 40.612...
180 181 11223 Brooklyn NY Brooklyn 36 047 0 31,424 58,702,923 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97299 40.60881, -73.96238 40.609...
181 182 11693 Far Rockaway NY Queens 36 081 0 6,887 1,527,599 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.83263 40.60841, -73.83292 40.608...
182 183 11692 Arverne NY Queens 36 081 0 31,673 23,992,395 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.79277 40.59995, -73.79219 40.600...
183 184 11235 Brooklyn NY Brooklyn 36 047 0 61,355 69,053,803 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.959 40.59178, -73.93301 40.59464...
184 185 11693 Far Rockaway NY Queens 36 081 0 19,052 12,270,917 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.81336 40.59096, -73.81315 40.591...
185 186 10306 Staten Island NY Staten Island 36 085 0 83,569 174,102,872 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.10179 40.58462, -74.09772 40.581...
186 187 11694 Rockaway Park NY Queens 36 081 0 46,740 48,101,607 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.81935 40.58787, -73.81953 40.587...
187 188 11224 Brooklyn NY Brooklyn 36 047 0 41,730 46,701,984 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.9665 40.58513, -73.96879 40.5752...
188 189 10308 Staten Island NY Staten Island 36 085 0 41,508 62,751,042 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.16589 40.56028, -74.165 40.56154...
189 190 11697 Breezy Point NY Queens 36 081 0 48,880 59,789,761 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.88323 40.56836, -73.88435 40.567...
190 191 10312 Staten Island NY Staten Island 36 085 0 65,792 169,087,433 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.19938 40.56041, -74.19367 40.565...
191 192 10309 Staten Island NY Staten Island 36 085 0 79,039 215,835,794 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.21312 40.55861, -74.21264 40.558...
192 193 10307 Staten Island NY Staten Island 36 085 0 31,375 46,028,383 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.24967 40.51555, -74.24823 40.516...
193 194 10280 New York NY Manhattan 36 061 0 8,192 2,234,114 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.01664 40.71217, -74.01568 40.711...
194 195 10048 New York NY Manhattan 36 061 0 4,034 972,788 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.01441 40.71099, -74.01375 40.713...
195 196 10279 New York NY Manhattan 36 061 1 681 28,665 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.00864 40.7126, -74.00851 40.7127...
196 197 10165 New York NY Manhattan 36 061 1 985 40,780 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97918 40.75214, -73.9795 40.7522...
197 198 10168 New York NY Manhattan 36 061 1 742 27,810 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97703 40.7513, -73.97687 40.7512...
198 199 10055 New York NY Manhattan 36 061 1 842 37,224 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97407 40.75926, -73.9739 40.7595...
199 200 10105 New York NY Manhattan 36 061 1 769 35,422 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97924 40.76283, -73.97953 40.762...
200 201 10118 New York NY Manhattan 36 061 1 1,393 91,734 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98673 40.74857, -73.98655 40.748...
201 202 10176 New York NY Manhattan 36 061 1 590 18,289 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.9787 40.7555, -73.97848 40.75541...
202 203 10162 New York NY Manhattan 36 061 1 625 21,035 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.95133 40.76931, -73.95165 40.769...
203 204 10019 New York NY Manhattan 36 061 0 24,983 18,828,383 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.9931 40.77273, -73.98477 40.7692...
204 205 10111 New York NY Manhattan 36 061 0 1,312 103,066 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97845 40.75907, -73.97799 40.759...
205 206 10170 New York NY Manhattan 36 061 1 1,000 61,793 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97631 40.7525, -73.97651 40.7525...
206 207 10112 New York NY Manhattan 36 061 1 521 16,701 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97274 40.75707, -73.97257 40.757...
207 208 10122 New York NY Manhattan 36 061 1 705 23,295 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.9921 40.75177, -73.99161 40.7521...
208 209 10107 New York NY Manhattan 36 061 1 717 23,030 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98299 40.7663, -73.98281 40.7665...
209 210 10103 New York NY Manhattan 36 061 1 1,038 62,713 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97724 40.76055, -73.97699 40.760...
210 211 10153 New York NY Manhattan 36 061 1 1,210 80,340 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97288 40.76411, -73.97164 40.763...
211 212 10174 New York NY Manhattan 36 061 1 842 44,203 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97574 40.75165, -73.97549 40.751...
212 213 10166 New York NY Manhattan 36 061 1 1,364 110,439 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97728 40.75351, -73.97681 40.754...
213 214 10169 New York NY Manhattan 36 061 1 1,113 66,246 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97669 40.75456, -73.97647 40.754...
214 215 10167 New York NY Manhattan 36 061 1 1,209 80,926 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97468 40.7543, -73.97553 40.7546...
215 216 10177 New York NY Manhattan 36 061 1 646 24,688 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97635 40.755, -73.976 40.75548, ...
216 217 10172 New York NY Manhattan 36 061 1 1,202 79,589 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97388 40.75538, -73.97347 40.755...
217 218 10171 New York NY Manhattan 36 061 1 614 23,525 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97408 40.75574, -73.97455 40.755...
218 219 10154 New York NY Manhattan 36 061 1 1,201 79,149 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97236 40.75743, -73.97325 40.757...
219 220 10152 New York NY Manhattan 36 061 1 1,005 59,925 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97147 40.75849, -73.97184 40.758...
220 221 10270 New York NY Manhattan 36 061 1 753 31,256 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.00822 40.70654, -74.00794 40.706...
221 222 10104 New York NY Manhattan 36 061 1 1,295 89,722 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97826 40.76005, -73.97835 40.759...
222 223 10271 New York NY Manhattan 36 061 1 940 49,237 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.01021 40.7083, -74.00994 40.7081...
223 224 10110 New York NY Manhattan 36 061 1 615 21,249 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98162 40.75395, -73.98145 40.754...
224 225 10175 New York NY Manhattan 36 061 1 574 18,685 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98 40.75441, -73.97943 40.75416,...
225 226 10151 New York NY Manhattan 36 061 1 630 21,380 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97359 40.76321, -73.97339 40.763...
226 227 10173 New York NY Manhattan 36 061 1 1,188 25,689 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97928 40.75403, -73.97912 40.753...
227 228 10178 New York NY Manhattan 36 061 1 944 51,303 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97729 40.7507, -73.97746 40.7504...
228 229 10119 New York NY Manhattan 36 061 1 1,679 126,393 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.99354 40.75145, -73.9932 40.7519...
229 230 10121 New York NY Manhattan 36 061 1 1,414 115,105 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.99213 40.75066, -73.99132 40.750...
230 231 10115 New York NY Manhattan 36 061 0 1,075 71,720 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.96442 40.81076, -73.96402 40.811...
231 232 10123 New York NY Manhattan 36 061 1 662 16,139 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.99059 40.75176, -73.99043 40.751...
232 233 10106 New York NY Manhattan 36 061 1 863 31,053 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98119 40.76553, -73.98101 40.765...
233 234 10158 New York NY Manhattan 36 061 1 777 35,396 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97543 40.74894, -73.97517 40.749...
234 235 10041 New York NY Manhattan 36 061 1 1,642 162,237 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.01025 40.70317, -74.00896 40.703...
235 236 10120 New York NY Manhattan 36 061 1 855 35,179 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98938 40.75001, -73.98908 40.749...
236 237 10278 New York NY Manhattan 36 061 1 1,889 206,706 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.00476 40.71507, -74.00531 40.715...
237 238 10155 New York NY Manhattan 36 061 1 839 24,785 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.96844 40.76111, -73.96833 40.761...
238 239 10022 New York NY Manhattan 36 061 0 14,672 12,728,336 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.97255 40.7649, -73.96268 40.7607...
239 240 10043 New York NY Manhattan 36 061 1 789 38,262 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.00708 40.70387, -74.0075 40.7042...
240 241 10081 New York NY Manhattan 36 061 1 778 30,241 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.00871 40.70749, -74.00949 40.707...
241 242 10096 New York NY Manhattan 36 061 1 851 42,106 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98302 40.75485, -73.98283 40.755...
242 243 10097 New York NY Manhattan 36 061 1 1,170 65,826 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98522 40.76265, -73.98412 40.762...
243 244 10196 New York NY Manhattan 36 061 1 721 32,502 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98243 40.7568, -73.98213 40.7572...
244 245 10196 New York NY Manhattan 36 061 1 289 3,155 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98133 40.75673, -73.98128 40.756...
245 246 10275 New York NY Manhattan 36 061 1 885 48,280 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.01451 40.70555, -74.01425 40.706...
246 247 10265 New York NY Manhattan 36 061 1 529 17,229 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.00806 40.70489, -74.00831 40.705...
247 248 10045 New York NY Manhattan 36 061 1 1,051 47,809 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.0091 40.70877, -74.00886 40.7089...
248 249 10047 New York NY Manhattan 36 061 1 545 10,150 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98633 40.73958, -73.98599 40.739...
249 250 10047 New York NY Manhattan 36 061 1 545 10,150 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98633 40.73958, -73.98599 40.739...
250 251 10080 New York NY Manhattan 36 061 1 1,313 77,111 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.01288 40.71052, -74.01259 40.710...
251 252 10203 New York NY Manhattan 36 061 1 910 37,227 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.01194 40.7072, -74.01166 40.7076...
252 253 10259 New York NY Manhattan 36 061 1 620 21,064 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.01036 40.70877, -74.01024 40.708...
253 254 10260 New York NY Manhattan 36 061 1 980 52,515 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.00908 40.70626, -74.0087 40.7066...
254 255 10285 New York NY Manhattan 36 061 1 1,068 67,350 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.01476 40.71309, -74.0155 40.7134...
255 256 10286 New York NY Manhattan 36 061 1 438 11,264 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.00936 40.70642, -74.00911 40.706...
256 257 11370 Bronx NY Bronx 36 005 0 17,838 18,190,205 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.89262 40.79246, -73.89274 40.792...
257 258 10065 New York NY Manhattan 36 061 0 15,542 11,442,580 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.95232 40.76454, -73.95442 40.762...
258 259 10075 New York NY Manhattan 36 061 0 13,541 4,809,655 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.94908 40.76828, -73.95052 40.768...
259 260 10069 New York NY Manhattan 36 061 0 7,781 2,372,366 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-73.98821 40.78123, -73.98675 40.780...
260 261 10281 New York NY Manhattan 36 061 0 4,717 958,087 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.01468 40.7098, -74.01638 40.7100...
261 262 10282 New York NY Manhattan 36 061 0 6,084 1,561,955 http://nyc.pediacities.com/Resource/PostalCode... POLYGON ((-74.01323 40.71832, -74.01421 40.713...
In [22]:
# Check how many Fortune500 Companies are located in New York City (turns out there are 43 Companies)
len(df.query("City == 'New York'"))
Out[22]:
43
In [23]:
# Draw the map of New York City (complete) in detail (interesting due to many Fortune500 Companies are located here)
m = None
m = folium.Map(location = [40.6455, -74.0821], zoom_start=11)
tooltip = folium.features.GeoJsonTooltip(fields=['borough','postalCode'], aliases=["Borough","Postal Code"], labels=True, stick=False)
folium.GeoJson(gdf2, tooltip=tooltip).add_to(m)
folium.LayerControl().add_to(m)
m
Out[23]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [24]:
# Using choropleth to give Color Map to the map.
m = None
m = folium.Map(location = [40.6455, -74.0821], zoom_start=11)
# The second Column for 'columns' (in this case: 'Shape_Leng') option must be numbers (int OR float)
cpleth = folium.Choropleth(gdf2, data=gdf2, key_on='feature.properties.postalCode', columns=['postalCode','Shape_Leng'], fill_color="RdYlGn", legend_name="Borough", name="New York City neighborhoods", line_opacity=1.0)
cpleth.geojson.add_child(tooltip)
cpleth.add_to(m)
folium.LayerControl().add_to(m)
m
Out[24]:
Make this Notebook Trusted to load map: File -> Trust Notebook

Statistics in State Level¶

In [25]:
# Grab all distinct State names
dfsts = df[['State']]
dfsts = dfsts.drop_duplicates()
dfsts = dfsts.reset_index(drop=True)
stslist = dfsts.to_numpy().tolist()
stslist[1][0]

for sts in stslist:
    print(sts[0])
    print("---------------")
Arkansas
---------------
Washington
---------------
Minnesota
---------------
California
---------------
Rhode Island
---------------
Nebraska
---------------
Texas
---------------
Pennsylvania
---------------
New York
---------------
Connecticut
---------------
Ohio
---------------
North Carolina
---------------
Michigan
---------------
Indiana
---------------
Missouri
---------------
Georgia
---------------
District of Columbia
---------------
Illinois
---------------
Virginia
---------------
Kentucky
---------------
New Jersey
---------------
Tennessee
---------------
Idaho
---------------
Maryland
---------------
Florida
---------------
Massachusetts
---------------
Oregon
---------------
Wisconsin
---------------
Colorado
---------------
Arizona
---------------
Oklahoma
---------------
Nevada
---------------
Iowa
---------------
Louisiana
---------------
Delaware
---------------
Alabama
---------------
Kansas
---------------
In [26]:
gdfsts
Out[26]:
State region postal latitude longitude geometry
0 Minnesota Midwest MN 46 -93 POLYGON ((-89.95766 47.28691, -90.13175 47.292...
1 Montana West MT 47 -110 POLYGON ((-116.04823 49.00037, -113.0595 49.00...
2 North Dakota Midwest ND 47 -100 POLYGON ((-97.22894 49.00089, -97.21414 48.902...
4 Idaho West ID 44 -114 POLYGON ((-116.04823 49.00037, -115.9678 47.95...
5 Washington West WA 47 -120 POLYGON ((-117.03143 48.99931, -117.02665 47.7...
6 Arizona West AZ 34 -112 POLYGON ((-109.04522 36.99991, -109.04367 31.3...
7 California West CA 37 -120 POLYGON ((-114.64222 35.05311, -114.62212 34.9...
8 Colorado West CO 39 -106 POLYGON ((-102.05017 40.00081, -102.04012 38.4...
9 Nevada West NV 39 -117 POLYGON ((-117.02825 42.00002, -114.03422 41.9...
10 New Mexico West NM 35 -106 POLYGON ((-109.04367 31.3419, -109.04522 36.99...
11 Oregon West OR 44 -120 POLYGON ((-116.915 45.99998, -116.679 45.80736...
12 Utah West UT 40 -112 POLYGON ((-114.03422 41.99312, -111.05024 42.0...
13 Wyoming West WY 43 -108 POLYGON ((-111.08518 44.50615, -111.06719 44.5...
14 Arkansas South AR 35 -92 POLYGON ((-89.66292 36.02307, -89.67351 35.94,...
15 Iowa Midwest IA 42 -93 POLYGON ((-96.45266 43.50179, -95.35994 43.500...
16 Kansas Midwest KS 38 -98 POLYGON ((-102.04118 36.99198, -102.04012 38.4...
17 Missouri Midwest MO 39 -92 POLYGON ((-89.66292 36.02307, -90.31539 36.023...
18 Nebraska Midwest NE 42 -100 POLYGON ((-102.05017 40.00081, -102.05017 40.0...
19 Oklahoma South OK 35 -97 POLYGON ((-103.00322 36.99516, -102.04118 36.9...
20 South Dakota Midwest SD 44 -100 POLYGON ((-96.53945 46.01797, -96.55689 45.872...
21 Louisiana South LA 31 -92 POLYGON ((-94.05976 33.01212, -93.09403 33.010...
22 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9...
23 Connecticut Northeast CT 42 -73 POLYGON ((-73.49794 42.05451, -72.73222 42.035...
24 Massachusetts Northeast MA 42 -72 POLYGON ((-71.80091 42.01325, -72.73222 42.035...
25 New Hampshire Northeast NH 44 -72 POLYGON ((-70.81505 42.86519, -70.9336 42.8842...
26 Rhode Island Northeast RI 42 -72 POLYGON ((-71.85383 41.32004, -71.79295 41.466...
27 Vermont Northeast VT 44 -73 POLYGON ((-72.45707 42.72708, -73.28203 42.743...
28 Alabama South AL 33 -87 POLYGON ((-88.16696 34.99967, -86.90968 34.999...
29 Florida South FL 28 -82 POLYGON ((-87.53039 30.2742, -87.45789 30.4112...
30 Georgia South GA 33 -83 POLYGON ((-85.00519 30.99069, -85.05442 31.108...
31 Mississippi South MS 33 -90 POLYGON ((-91.15624 33.01, -91.10808 33.20684,...
32 South Carolina South SC 34 -81 POLYGON ((-80.86501 32.03316, -81.03644 32.084...
33 Illinois Midwest IL 40 -89 POLYGON ((-91.43033 40.3686, -91.41023 40.5511...
34 Indiana Midwest IN 40 -86 POLYGON ((-88.05108 37.8196, -88.01881 38.0217...
35 Kentucky South KY 37 -86 POLYGON ((-89.49836 36.5062, -89.27398 36.6115...
36 North Carolina South NC 36 -79 POLYGON ((-83.07637 34.97903, -84.32097 34.986...
37 Ohio Midwest OH 40 -83 POLYGON ((-84.82368 39.10653, -84.81787 39.799...
38 Tennessee South TN 36 -86 POLYGON ((-90.24924 35.02083, -90.13493 35.113...
39 Virginia South VA 38 -78 MULTIPOLYGON (((-83.33059 36.67266, -83.17851 ...
40 Wisconsin Midwest WI 44 -90 POLYGON ((-91.2282 43.50125, -91.25466 43.6139...
41 West Virginia South WV 39 -81 POLYGON ((-81.97254 37.53595, -82.16728 37.554...
42 Delaware South DE 39 -75 POLYGON ((-75.04839 38.44876, -75.71462 38.449...
43 District of Columbia South DC 39 -77 POLYGON ((-77.04124 38.78954, -77.04123 38.789...
44 Maryland South MD 39 -77 POLYGON ((-75.37754 38.01538, -75.37754 38.015...
45 New Jersey Northeast NJ 40 -74 POLYGON ((-75.52781 39.49865, -75.55427 39.691...
46 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289...
47 Pennsylvania Northeast PA 41 -78 POLYGON ((-80.51893 40.64111, -80.51627 42.324...
48 Maine Northeast ME 45 -69 POLYGON ((-70.64573 43.09008, -70.75102 43.080...
49 Michigan Midwest MI 43 -85 POLYGON ((-89.95766 47.28691, -89.84283 47.464...
In [27]:
# Check the Largest Revenue Company in each State
dfmaxrevco = df.head(1)

for st in stslist[0:]:
    dfst = df.where(df['State'] == st[0]).dropna()
    mnmaxrev = dfst['Revenue (rounded)'].max()
    dfstmaxrevco = dfst.where(dfst['Revenue (rounded)'] == mnmaxrev).dropna()
    #dfstmaxrevco[['Rank']] = int(dfstmaxrevco['Rank'].iloc[0])
    dfstmaxrevco[['Zip Code']] = int(dfstmaxrevco['Zip Code'].iloc[0])
    #print(dfstmaxrevco)
    dfmaxrevco = pd.concat([dfmaxrevco, dfstmaxrevco], ignore_index=True)
    
dfmaxrevco = dfmaxrevco.drop(0)
dfmaxrevco[['State','Company','Industry','City','Zip Code','Revenue (rounded)']].sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
Out[27]:
State Company Industry City Zip Code Revenue (rounded)
0 Arkansas Walmart General Merchandisers Bentonville 72712 681,000,000,000
1 Washington Amazon Internet Services and Retailing Seattle 98109 638,000,000,000
2 Minnesota UnitedHealth Health Care: Insurance and Managed Care Eden Prairie 55344 400,300,000,000
3 California Apple Computers, Office Equipment Cupertino 95014 391,000,000,000
4 Rhode Island CVS Health Health Care: Pharmacy and Other Services Woonsocket 2895 372,800,000,000
5 Nebraska Berkshire Hathaway Insurance: Property and Casualty (Stock) Omaha 68131 371,400,000,000
6 Texas Exxon Mobil Petroleum Refining Spring 77389 349,600,000,000
7 Pennsylvania Cencora Wholesalers: Health Care Conshohocken 19428 294,000,000,000
8 New York JPMorgan Chase Commercial Banks New York 10017 278,900,000,000
9 Connecticut Cigna Health Care: Pharmacy and Other Services Bloomfield 6002 247,100,000,000
10 Ohio Cardinal Health Wholesalers: Health Care Dublin 43017 226,800,000,000
11 North Carolina Bank of America Commercial Banks Charlotte 28255 192,400,000,000
12 Michigan General Motors Motor Vehicles & Parts Detroit 48265 187,400,000,000
13 Indiana Elevance Health Health Care: Insurance and Managed Care Indianapolis 46204 177,000,000,000
14 Missouri Centene Health Care: Insurance and Managed Care St. Louis 63105 163,100,000,000
15 Georgia Home Depot Specialty Retailers: Other Atlanta 30339 159,500,000,000
16 District of Columbia Fannie Mae Diversified Financials Washington 20005 152,700,000,000
17 Illinois Walgreens Food & Drug Stores Deerfield 60015 147,700,000,000
18 Virginia Freddie Mac Diversified Financials McLean 22102 122,100,000,000
19 Kentucky Humana Health Care: Insurance and Managed Care Louisville 40202 117,800,000,000
20 New Jersey Johnson & Johnson Pharmaceuticals New Brunswick 8933 88,800,000,000
21 Tennessee FedEx Mail, Package and Freight Delivery Memphis 38120 87,700,000,000
22 Idaho Albertsons Food & Drug Stores Boise 83706 79,200,000,000
23 Maryland Lockheed Martin Aerospace & Defense Bethesda 20817 71,000,000,000
24 Florida Publix Super Markets Food & Drug Stores Lakeland 33811 60,200,000,000
25 Massachusetts TJX Specialty Retailers: Apparel Framingham 1701 56,400,000,000
26 Oregon Nike Apparel Beaverton 97005 51,400,000,000
27 Wisconsin Northwestern Mutual Insurance: Life, Health (Mutual) Milwaukee 53202 41,400,000,000
28 Colorado Arrow Electronics Wholesalers: Electronics and Office Equipment Centennial 80112 27,900,000,000
29 Arizona Freeport-McMoRan Mining, Crude-Oil Production Phoenix 85004 25,500,000,000
30 Oklahoma Oneok Pipelines Tulsa 74103 21,700,000,000
31 Nevada MGM Resorts International Hotels, Casinos, Resorts Las Vegas 89109 17,200,000,000
32 Iowa Principal Financial Insurance: Life, Health (Stock) Des Moines 50392 16,100,000,000
33 Louisiana Lumen Technologies Telecommunications Monroe 71203 13,100,000,000
34 Delaware DuPont Chemicals Wilmington 19805 12,400,000,000
35 Alabama Regions Financial Commercial Banks Birmingham 35203 9,400,000,000
36 Kansas Seaboard Food Production Merriam 66202 9,100,000,000
In [28]:
# Draw the Map of the Largest Revenue Companies in each State
# Join the Dataframe 'gdfsts500' with 'dfmaxrevco'
gdfstsmaxrevco = gdfsts.merge(dfmaxrevco, how = 'inner', on = ['State'])
# ,'Company','Industry','Zip Code','Website','Employees'
gdfstsmaxrevco.head(2)
Out[28]:
State region postal latitude longitude geometry Company Industry City Zip Code Website Employees Revenue (rounded) CEO
0 Minnesota Midwest MN 46 -93 POLYGON ((-89.95766 47.28691, -90.13175 47.292... UnitedHealth Health Care: Insurance and Managed Care Eden Prairie 55344 unitedhealthgroup.com 400,000 400,300,000,000 Stephen Hemsley
1 Idaho West ID 44 -114 POLYGON ((-116.04823 49.00037, -115.9678 47.95... Albertsons Food & Drug Stores Boise 83706 albertsonscompanies.com 196,600 79,200,000,000 Susan Morris
In [29]:
m = gdfstsmaxrevco.explore(column='Revenue (rounded)', name='Biggest Revenue Company in each State', cmap='RdYlGn', edgecolor='black', legend_name="Revenue")
folium.LayerControl().add_to(m)
m
Out[29]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [30]:
# Check the Smallest Revenue Company in each State
dfminrevco = df.head(1)

for st in stslist[0:]:
    dfst = df.where(df['State'] == st[0]).dropna()
    mnminrev = dfst['Revenue (rounded)'].min()
    dfstminrevco = dfst.where(dfst['Revenue (rounded)'] == mnminrev).dropna()
    dfstminrevco[['Zip Code']] = int(dfstminrevco['Zip Code'].iloc[0])
    dfminrevco = pd.concat([dfminrevco, dfstminrevco], ignore_index=True)
    
dfminrevco = dfminrevco.drop(0)
dfminrevco[['State','Company','Industry','City','Zip Code','Revenue (rounded)']].sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
Out[30]:
State Company Industry City Zip Code Revenue (rounded)
0 Oregon Lithia Motors Automotive Retailing, Services Medford 97501 36,600,000,000
1 Idaho Micron Technology Semiconductors and Other Electronic Components Boise 83716 25,100,000,000
2 Maryland Constellation Energy Energy Baltimore 21231 23,600,000,000
3 Iowa Casey's General Stores Specialty Retailers: Other Ankeny 50021 14,900,000,000
4 Nebraska Mutual of Omaha Insurance Insurance: Life, Health (Mutual) Omaha 68175 14,600,000,000
5 Delaware DuPont Chemicals Wilmington 19805 12,400,000,000
6 Arkansas J.B. Hunt Transport Services Trucking, Truck Leasing Lowell 72745 12,100,000,000
7 Louisiana Entergy Utilities: Gas and Electric New Orleans 70113 11,900,000,000
8 Nevada Las Vegas Sands Hotels, Casinos, Resorts Las Vegas 89113 11,300,000,000
9 Nevada Caesars Entertainment Hotels, Casinos, Resorts Reno 89113 11,300,000,000
10 North Carolina Advance Auto Parts Specialty Retailers: Other Raleigh 27609 10,900,000,000
11 Washington Expeditors International of Washington Transportation and Logistics Bellevue 98006 10,600,000,000
12 Washington Lululemon athletica Specialty Retailers: Apparel Sumner 98006 10,600,000,000
13 Oklahoma Williams Pipelines Tulsa 74172 10,500,000,000
14 Rhode Island FM Insurance: Property and Casualty (Stock) Johnston 2919 10,400,000,000
15 Massachusetts Analog Devices Semiconductors and Other Electronic Components Wilmington 1887 9,400,000,000
16 Tennessee Eastman Chemical Chemicals Kingsport 37660 9,400,000,000
17 New Jersey Zoetis Pharmaceuticals Parsippany 7054 9,300,000,000
18 Colorado Ovintiv Mining, Crude-Oil Production Denver 80202 9,200,000,000
19 Kansas Seaboard Food Production Merriam 66202 9,100,000,000
20 District of Columbia Xylem Industrial Machinery Washington 20003 8,600,000,000
21 Wisconsin Rockwell Automation Electronics, Electrical Equip. Milwaukee 53204 8,300,000,000
22 Connecticut XPO Transportation and Logistics Greenwich 6831 8,100,000,000
23 New York Foot Locker Specialty Retailers: Apparel New York 10169 8,000,000,000
24 New York Voya Financial Diversified Financials New York 10169 8,000,000,000
25 Ohio TransDigm Aerospace & Defense Cleveland 44115 7,900,000,000
26 Texas KBR Information Technology Services Houston 77002 7,700,000,000
27 Indiana Zimmer Biomet s Medical Products and Equipment Warsaw 46580 7,700,000,000
28 Florida Watsco Wholesalers: Diversified Miami 33133 7,600,000,000
29 Georgia Newell Brands Home Equipment, Furnishings Atlanta 30328 7,600,000,000
30 Arizona Microchip Technology Semiconductors and Other Electronic Components Chandler 85224 7,600,000,000
31 Minnesota Fastenal Wholesalers: Diversified Winona 55987 7,500,000,000
32 California Monster Beverage Beverages Corona 92879 7,500,000,000
33 California Endeavor Entertainment Beverly Hills 92879 7,500,000,000
34 Kentucky Yum Brands Food Services Louisville 40213 7,500,000,000
35 Virginia Science Applications International Information Technology Services Reston 20190 7,500,000,000
36 Michigan CMS Energy Utilities: Gas and Electric Jackson 49201 7,500,000,000
37 Pennsylvania Howmet Aerospace Aerospace & Defense Pittsburgh 15212 7,400,000,000
38 Missouri Core & Main Wholesalers: Diversified St. Louis 63146 7,400,000,000
39 Alabama Vulcan Materials Building Materials, Glass Birmingham 35242 7,400,000,000
40 Illinois Ingredion Food Production Westchester 60154 7,400,000,000
In [31]:
# Draw the Map of the Smallest Revenue Company in each State
# Join the Dataframe 'gdfsts' with 'dfminrevco'
gdfstsminrevco = gdfsts.merge(dfminrevco, how = 'inner', on = ['State'])
gdfstsminrevco.head(2)
Out[31]:
State region postal latitude longitude geometry Company Industry City Zip Code Website Employees Revenue (rounded) CEO
0 Minnesota Midwest MN 46 -93 POLYGON ((-89.95766 47.28691, -90.13175 47.292... Fastenal Wholesalers: Diversified Winona 55987 fastenal.com 21,000 7,500,000,000 Daniel Florness
1 Idaho West ID 44 -114 POLYGON ((-116.04823 49.00037, -115.9678 47.95... Micron Technology Semiconductors and Other Electronic Components Boise 83716 micron.com 48,000 25,100,000,000 Sanjay Mehrotra
In [32]:
mminrevco = gdfstsminrevco.explore(column='Revenue (rounded)', name='Smallest Revenue Company in each State', cmap='RdYlGn', edgecolor='black')
folium.LayerControl().add_to(mminrevco)
mminrevco
Out[32]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [33]:
# Check the Total Revenue in each State
dfsttr = df.groupby('State')[df.columns[[7]]].sum('Revenue (rounded)').sort_values('Revenue (rounded)', ascending=False)
dfsttr
Out[33]:
Revenue (rounded)
State
Texas 2,680,800,000,000
California 2,399,300,000,000
New York 2,085,200,000,000
Washington 1,299,400,000,000
Illinois 1,040,200,000,000
Ohio 1,035,800,000,000
Minnesota 802,600,000,000
Arkansas 764,300,000,000
Virginia 738,400,000,000
Pennsylvania 672,400,000,000
Michigan 602,400,000,000
Georgia 548,300,000,000
Connecticut 532,100,000,000
North Carolina 469,300,000,000
Florida 448,700,000,000
New Jersey 440,900,000,000
Rhode Island 440,300,000,000
Nebraska 427,000,000,000
Massachusetts 384,500,000,000
Indiana 320,500,000,000
Tennessee 312,700,000,000
Missouri 262,600,000,000
District of Columbia 185,200,000,000
Wisconsin 144,900,000,000
Kentucky 136,600,000,000
Arizona 125,000,000,000
Maryland 119,700,000,000
Colorado 117,000,000,000
Idaho 104,300,000,000
Oregon 88,000,000,000
Oklahoma 48,100,000,000
Nevada 39,800,000,000
Iowa 31,000,000,000
Louisiana 25,000,000,000
Alabama 16,800,000,000
Delaware 12,400,000,000
Kansas 9,100,000,000
In [34]:
# Draw the Map of Total Revenue in each State
# Join the Dataframe 'gdfsts' with 'dfsttr'
gdfststotrevco = gdfsts.merge(dfsttr, how = 'inner', on = ['State'])
gdfststotrevco.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
Out[34]:
State region postal latitude longitude geometry Revenue (rounded)
0 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... 2,680,800,000,000
1 California West CA 37 -120 POLYGON ((-114.64222 35.05311, -114.62212 34.9... 2,399,300,000,000
2 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... 2,085,200,000,000
3 Washington West WA 47 -120 POLYGON ((-117.03143 48.99931, -117.02665 47.7... 1,299,400,000,000
4 Illinois Midwest IL 40 -89 POLYGON ((-91.43033 40.3686, -91.41023 40.5511... 1,040,200,000,000
5 Ohio Midwest OH 40 -83 POLYGON ((-84.82368 39.10653, -84.81787 39.799... 1,035,800,000,000
6 Minnesota Midwest MN 46 -93 POLYGON ((-89.95766 47.28691, -90.13175 47.292... 802,600,000,000
7 Arkansas South AR 35 -92 POLYGON ((-89.66292 36.02307, -89.67351 35.94,... 764,300,000,000
8 Virginia South VA 38 -78 MULTIPOLYGON (((-83.33059 36.67266, -83.17851 ... 738,400,000,000
9 Pennsylvania Northeast PA 41 -78 POLYGON ((-80.51893 40.64111, -80.51627 42.324... 672,400,000,000
10 Michigan Midwest MI 43 -85 POLYGON ((-89.95766 47.28691, -89.84283 47.464... 602,400,000,000
11 Georgia South GA 33 -83 POLYGON ((-85.00519 30.99069, -85.05442 31.108... 548,300,000,000
12 Connecticut Northeast CT 42 -73 POLYGON ((-73.49794 42.05451, -72.73222 42.035... 532,100,000,000
13 North Carolina South NC 36 -79 POLYGON ((-83.07637 34.97903, -84.32097 34.986... 469,300,000,000
14 Florida South FL 28 -82 POLYGON ((-87.53039 30.2742, -87.45789 30.4112... 448,700,000,000
15 New Jersey Northeast NJ 40 -74 POLYGON ((-75.52781 39.49865, -75.55427 39.691... 440,900,000,000
16 Rhode Island Northeast RI 42 -72 POLYGON ((-71.85383 41.32004, -71.79295 41.466... 440,300,000,000
17 Nebraska Midwest NE 42 -100 POLYGON ((-102.05017 40.00081, -102.05017 40.0... 427,000,000,000
18 Massachusetts Northeast MA 42 -72 POLYGON ((-71.80091 42.01325, -72.73222 42.035... 384,500,000,000
19 Indiana Midwest IN 40 -86 POLYGON ((-88.05108 37.8196, -88.01881 38.0217... 320,500,000,000
20 Tennessee South TN 36 -86 POLYGON ((-90.24924 35.02083, -90.13493 35.113... 312,700,000,000
21 Missouri Midwest MO 39 -92 POLYGON ((-89.66292 36.02307, -90.31539 36.023... 262,600,000,000
22 District of Columbia South DC 39 -77 POLYGON ((-77.04124 38.78954, -77.04123 38.789... 185,200,000,000
23 Wisconsin Midwest WI 44 -90 POLYGON ((-91.2282 43.50125, -91.25466 43.6139... 144,900,000,000
24 Kentucky South KY 37 -86 POLYGON ((-89.49836 36.5062, -89.27398 36.6115... 136,600,000,000
25 Arizona West AZ 34 -112 POLYGON ((-109.04522 36.99991, -109.04367 31.3... 125,000,000,000
26 Maryland South MD 39 -77 POLYGON ((-75.37754 38.01538, -75.37754 38.015... 119,700,000,000
27 Colorado West CO 39 -106 POLYGON ((-102.05017 40.00081, -102.04012 38.4... 117,000,000,000
28 Idaho West ID 44 -114 POLYGON ((-116.04823 49.00037, -115.9678 47.95... 104,300,000,000
29 Oregon West OR 44 -120 POLYGON ((-116.915 45.99998, -116.679 45.80736... 88,000,000,000
30 Oklahoma South OK 35 -97 POLYGON ((-103.00322 36.99516, -102.04118 36.9... 48,100,000,000
31 Nevada West NV 39 -117 POLYGON ((-117.02825 42.00002, -114.03422 41.9... 39,800,000,000
32 Iowa Midwest IA 42 -93 POLYGON ((-96.45266 43.50179, -95.35994 43.500... 31,000,000,000
33 Louisiana South LA 31 -92 POLYGON ((-94.05976 33.01212, -93.09403 33.010... 25,000,000,000
34 Alabama South AL 33 -87 POLYGON ((-88.16696 34.99967, -86.90968 34.999... 16,800,000,000
35 Delaware South DE 39 -75 POLYGON ((-75.04839 38.44876, -75.71462 38.449... 12,400,000,000
36 Kansas Midwest KS 38 -98 POLYGON ((-102.04118 36.99198, -102.04012 38.4... 9,100,000,000
In [35]:
mtotrevco = gdfststotrevco.explore(column='Revenue (rounded)', name='Total Revenue of States', cmap='RdYlGn', edgecolor='black')
folium.LayerControl().add_to(mtotrevco)
mtotrevco
Out[35]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [36]:
# Average revenue in each State
dfstavrrev = df.groupby('State')[df.columns[[7]]].mean().sort_values('Revenue (rounded)', ascending=False)
dfstavrrev
Out[36]:
Revenue (rounded)
State
Arkansas 191,075,000,000
Washington 118,127,272,727
Nebraska 106,750,000,000
Rhode Island 88,060,000,000
District of Columbia 61,733,333,333
Idaho 52,150,000,000
Texas 49,644,444,444
Minnesota 47,211,764,706
Kentucky 45,533,333,333
Oregon 44,000,000,000
North Carolina 42,663,636,364
California 41,367,241,379
Michigan 40,160,000,000
Indiana 40,062,500,000
Maryland 39,900,000,000
New York 39,343,396,226
Ohio 36,992,857,143
Connecticut 35,473,333,333
Pennsylvania 35,389,473,684
Missouri 32,825,000,000
Illinois 32,506,250,000
Georgia 32,252,941,176
Virginia 29,536,000,000
New Jersey 29,393,333,333
Tennessee 28,427,272,727
Massachusetts 24,031,250,000
Florida 20,395,454,545
Wisconsin 18,112,500,000
Oklahoma 16,033,333,333
Iowa 15,500,000,000
Colorado 14,625,000,000
Arizona 13,888,888,889
Nevada 13,266,666,667
Louisiana 12,500,000,000
Delaware 12,400,000,000
Kansas 9,100,000,000
Alabama 8,400,000,000
In [37]:
# Draw the Map of the Average Revenue of Companies in each State
# Join the Dataframe 'gdfsts' with 'dfstavr'
gdfstsstavrrev = gdfsts.merge(dfstavrrev, how = 'inner', on = ['State'])
gdfstsstavrrev.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True).head(2)
Out[37]:
State region postal latitude longitude geometry Revenue (rounded)
0 Arkansas South AR 35 -92 POLYGON ((-89.66292 36.02307, -89.67351 35.94,... 191,075,000,000
1 Washington West WA 47 -120 POLYGON ((-117.03143 48.99931, -117.02665 47.7... 118,127,272,727
In [38]:
mstavrrev = gdfstsstavrrev.explore(column='Revenue (rounded)', name='Average Revenue of Companies in each State', cmap='RdYlGn', edgecolor='black')
folium.LayerControl().add_to(mstavrrev)
mstavrrev
Out[38]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [39]:
# Largest Employer Company in each State
dfmaxempco = df.head(1)

for st in stslist[0:]:
    dfst = df.where(df['State'] == st[0]).dropna()
    mnmaxemp = dfst['Employees'].max()
    dfstmaxempco = dfst.where(dfst['Employees'] == mnmaxemp).dropna()
    dfmaxempco = pd.concat([dfmaxempco, dfstmaxempco], ignore_index=True)
    
dfmaxempco = dfmaxempco.drop(0)
#dfmaxempco['Employees'] = df['Employees'].astype(int)
dfmaxempco[['State','Company','Industry','City','Zip Code','Employees']].sort_values(by='Employees', ascending=False).reset_index(drop=True)
Out[39]:
State Company Industry City Zip Code Employees
0 Arkansas Walmart General Merchandisers Bentonville 72712 2,100,000
1 Washington Amazon Internet Services and Retailing Seattle 98109 1,556,000
2 Georgia Home Depot Specialty Retailers: Other Atlanta 30339 470,100
3 California Concentrix Information Technology Services Newark 94560 450,000
4 Minnesota Target General Merchandisers Minneapolis 55403 440,000
5 Tennessee FedEx Mail, Package and Freight Delivery Memphis 38120 422,100
6 Ohio Kroger Food & Drug Stores Cincinnati 45202 409,000
7 Nebraska Berkshire Hathaway Insurance: Property and Casualty (Stock) Omaha 68131 392,400
8 Massachusetts TJX Specialty Retailers: Apparel Framingham 01701 364,000
9 New Jersey Cognizant Technology Information Technology Services Teaneck 07666 336,800
10 New York PepsiCo Food Consumer Products Purchase 10577 319,000
11 Pennsylvania Aramark Diversified Outsourcing Services Philadelphia 19103 266,700
12 Rhode Island CVS Health Health Care: Pharmacy and Other Services Woonsocket 02895 259,500
13 Florida Publix Super Markets Food & Drug Stores Lakeland 33811 255,000
14 Illinois Walgreens Food & Drug Stores Deerfield 60015 252,500
15 Texas Yum China s Food Services Plano 75074 245,500
16 North Carolina Lowe's Specialty Retailers: Other Mooresville 28117 215,500
17 Idaho Albertsons Food & Drug Stores Boise 83706 196,600
18 Virginia RTX Aerospace & Defense Arlington 22209 186,000
19 Michigan Lear Motor Vehicles & Parts Southfield 48033 173,700
20 Maryland Marriott International Hotels, Casinos, Resorts Bethesda 20814 155,000
21 Connecticut GXO Logistics Transportation and Logistics Greenwich 06831 128,500
22 Indiana Elevance Health Health Care: Insurance and Managed Care Indianapolis 46204 103,700
23 Missouri O'Reilly Automotive Specialty Retailers: Other Springfield 65802 85,600
24 Oregon Nike Apparel Beaverton 97005 79,400
25 Colorado DaVita Health Care: Medical Facilities Denver 80202 76,000
26 Nevada MGM Resorts International Hotels, Casinos, Resorts Las Vegas 89109 69,000
27 Kentucky Humana Health Care: Insurance and Managed Care Louisville 40202 65,700
28 District of Columbia Danaher Medical Products and Equipment Washington 20037 62,000
29 Wisconsin Kohl's General Merchandisers Menomonee Falls 53051 60,000
30 Arizona Republic Services Waste Management Phoenix 85054 42,000
31 Iowa Casey's General Stores Specialty Retailers: Other Ankeny 50021 33,100
32 Louisiana Lumen Technologies Telecommunications Monroe 71203 25,000
33 Delaware DuPont Chemicals Wilmington 19805 24,000
34 Alabama Regions Financial Commercial Banks Birmingham 35203 19,600
35 Kansas Seaboard Food Production Merriam 66202 14,000
36 Oklahoma Williams Pipelines Tulsa 74172 5,800
In [40]:
# The Biggest Employer Company in each State.
# Join the Dataframe 'gdfsts' with 'dfmaxempco'
gdfstsmaxempco = gdfsts.merge(dfmaxempco, how = 'inner', on = ['State'])
gdfstsmaxempco.head(2)
Out[40]:
State region postal latitude longitude geometry Company Industry City Zip Code Website Employees Revenue (rounded) CEO
0 Minnesota Midwest MN 46 -93 POLYGON ((-89.95766 47.28691, -90.13175 47.292... Target General Merchandisers Minneapolis 55403 target.com 440,000 106,600,000,000 Brian Cornell
1 Idaho West ID 44 -114 POLYGON ((-116.04823 49.00037, -115.9678 47.95... Albertsons Food & Drug Stores Boise 83706 albertsonscompanies.com 196,600 79,200,000,000 Susan Morris
In [41]:
mmaxempco = gdfstsmaxempco.explore(column='Employees', name='Biggest Employer Company in each State', cmap='RdYlGn', edgecolor='black')
folium.LayerControl().add_to(mmaxempco)
mmaxempco
Out[41]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [42]:
# Smallest Employer Company in each State
dfminempco = df.head(1)

for st in stslist[0:]:
    dfst = df.where(df['State'] == st[0]).dropna()
    mnminemp = dfst['Employees'].min()
    dfstminempco = dfst.where(dfst['Employees'] == mnminemp).dropna()
    dfminempco = pd.concat([dfminempco, dfstminempco], ignore_index=True)
    
dfminempco = dfminempco.drop(0)
dfminempco[['State','Company','Industry','City','Zip Code','Employees']].sort_values(by='Employees', ascending=False).reset_index(drop=True)
Out[42]:
State Company Industry City Zip Code Employees
0 Idaho Micron Technology Semiconductors and Other Electronic Components Boise 83716 48,000
1 Nevada Las Vegas Sands Hotels, Casinos, Resorts Las Vegas 89113 40,100
2 Kentucky Yum Brands Food Services Louisville 40213 31,700
3 Oregon Lithia Motors Automotive Retailing, Services Medford 97501 30,200
4 Delaware DuPont Chemicals Wilmington 19805 24,000
5 Iowa Principal Financial Insurance: Life, Health (Stock) Des Moines 50392 19,700
6 Washington Expedia Internet Services and Retailing Seattle 98119 16,500
7 Maryland Constellation Energy Energy Baltimore 21231 14,200
8 Kansas Seaboard Food Production Merriam 66202 14,000
9 Indiana Steel Dynamics Metals Fort Wayne 46804 13,000
10 Louisiana Entergy Utilities: Gas and Electric New Orleans 70113 12,300
11 Alabama Vulcan Materials Building Materials, Glass Birmingham 35242 12,000
12 Arkansas Murphy USA Specialty Retailers: Other El Dorado 71730 11,600
13 North Carolina Sonic Automotive Automotive Retailing, Services Charlotte 28211 10,800
14 Illinois Old Republic International Insurance: Property and Casualty (Stock) Chicago 60601 9,400
15 District of Columbia Fannie Mae Diversified Financials Washington 20005 8,200
16 Michigan Auto-Owners Insurance Insurance: Property and Casualty (Mutual) Lansing 48917 7,300
17 Wisconsin WEC Energy Utilities: Gas and Electric Milwaukee 53203 7,000
18 Georgia Pulte Homebuilders Atlanta 30326 6,800
19 Nebraska Mutual of Omaha Insurance Insurance: Life, Health (Mutual) Omaha 68175 6,500
20 Virginia Altria Tobacco Richmond 23230 6,200
21 Rhode Island FM Insurance: Property and Casualty (Stock) Johnston 02919 5,800
22 Pennsylvania Toll Brothers Homebuilders Fort Washington 19034 4,900
23 Florida World Kinect Energy Miami 33178 4,700
24 Missouri Reinsurance of America Insurance: Life, Health (Stock) Chesterfield 63017 4,100
25 Minnesota Thrivent Financial for Lutherans Insurance: Life, Health (Mutual) Minneapolis 55415 4,000
26 New Jersey PBF Energy Petroleum Refining Parsippany 07054 3,900
27 Massachusetts Global Partners Energy Waltham 02453 3,800
28 Connecticut Interactive Brokers Securities Greenwich 06830 3,000
29 Arizona Taylor Morrison Home Homebuilders Scottsdale 85251 3,000
30 Oklahoma Devon Energy Mining, Crude-Oil Production Oklahoma City 73102 2,300
31 Tennessee Delek US Petroleum Refining Brentwood 37027 2,000
32 New York Hess Mining, Crude-Oil Production New York 10036 1,800
33 Texas Cheniere Energy Pipelines Houston 77002 1,700
34 Colorado Ovintiv Mining, Crude-Oil Production Denver 80202 1,600
35 Ohio Welltower Real Estate Toledo 43615 700
36 California A-Mark Precious Metals Wholesalers: Diversified El Segundo 90245 500
In [43]:
# The Smallest Employer Company in each State.
# Join the Dataframe 'gdfsts' with 'dfminempco'
gdfstsminempco = gdfsts.merge(dfminempco, how = 'inner', on = ['State'])
gdfstsminempco.head(2)
Out[43]:
State region postal latitude longitude geometry Company Industry City Zip Code Website Employees Revenue (rounded) CEO
0 Minnesota Midwest MN 46 -93 POLYGON ((-89.95766 47.28691, -90.13175 47.292... Thrivent Financial for Lutherans Insurance: Life, Health (Mutual) Minneapolis 55415 thrivent.com 4,000 10,900,000,000 Teresa Rasmussen
1 Idaho West ID 44 -114 POLYGON ((-116.04823 49.00037, -115.9678 47.95... Micron Technology Semiconductors and Other Electronic Components Boise 83716 micron.com 48,000 25,100,000,000 Sanjay Mehrotra
In [44]:
mminempco = gdfstsminempco.explore(column='Employees', name='Smallest Employer Company in each State', cmap='RdYlGn', edgecolor='black')
folium.LayerControl().add_to(mminempco)
mminempco
Out[44]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [155]:
# Check Total Employee in each State
dfstte = df.groupby('State').sum('Employees').sort_values('Employees', ascending=False)
dfstte
Out[155]:
Employees Revenue (rounded)
State
California 2857700 2,399,300,000,000
New York 2825500 2,085,200,000,000
Washington 2750600 1,299,400,000,000
Texas 2432800 2,680,800,000,000
Arkansas 2283200 764,300,000,000
Illinois 1655400 1,040,200,000,000
Virginia 1461200 738,400,000,000
Georgia 1327300 548,300,000,000
Minnesota 1269900 802,600,000,000
Ohio 1255100 1,035,800,000,000
Tennessee 1190500 312,700,000,000
Florida 1058700 448,700,000,000
New Jersey 944300 440,900,000,000
Pennsylvania 929200 672,400,000,000
North Carolina 856900 469,300,000,000
Massachusetts 854000 384,500,000,000
Michigan 838000 602,400,000,000
Connecticut 806700 532,100,000,000
Nebraska 463100 427,000,000,000
Rhode Island 344900 440,300,000,000
Indiana 336600 320,500,000,000
Missouri 305400 262,600,000,000
Maryland 290200 119,700,000,000
Idaho 244600 104,300,000,000
Wisconsin 196500 144,900,000,000
Arizona 194000 125,000,000,000
Colorado 194000 117,000,000,000
Nevada 159100 39,800,000,000
Kentucky 134400 136,600,000,000
Oregon 109600 88,000,000,000
District of Columbia 93200 185,200,000,000
Iowa 52800 31,000,000,000
Louisiana 37300 25,000,000,000
Alabama 31600 16,800,000,000
Delaware 24000 12,400,000,000
Kansas 14000 9,100,000,000
Oklahoma 13300 48,100,000,000
In [156]:
# Map of Total Employee in each State.
# Join the Dataframe 'gdfsts' with 'dfstte'
gdfstsstte = gdfsts.merge(dfstte, how = 'inner', on = ['State'])
gdfstsstte.head(2)
Out[156]:
State region postal latitude longitude geometry Employees Revenue (rounded)
0 Minnesota Midwest MN 46 -93 POLYGON ((-89.95766 47.28691, -90.13175 47.292... 1269900 802,600,000,000
1 Idaho West ID 44 -114 POLYGON ((-116.04823 49.00037, -115.9678 47.95... 244600 104,300,000,000
In [157]:
mstte = gdfstsstte.explore(column='Employees', name='Total Employee in each State', cmap='RdYlGn', edgecolor='black')
folium.LayerControl().add_to(mstte)
mstte
Out[157]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [48]:
# Check Average Number of Employee in each State
dfstavremp = df.groupby('State')[df.columns[[6]]].mean('Employees').sort_values('Employees', ascending=False)
dfstavremp
Out[48]:
Employees
State
Arkansas 570,800
Washington 250,055
Idaho 122,300
Nebraska 115,775
Tennessee 108,227
Maryland 96,733
Georgia 78,076
North Carolina 77,900
Minnesota 74,700
Rhode Island 68,980
New Jersey 62,953
Virginia 58,448
Michigan 55,867
Oregon 54,800
Connecticut 53,780
Massachusetts 53,375
New York 53,311
Nevada 53,033
Illinois 51,731
California 49,271
Pennsylvania 48,905
Florida 48,123
Texas 45,052
Ohio 44,825
Kentucky 44,800
Indiana 42,075
Missouri 38,175
District of Columbia 31,067
Iowa 26,400
Wisconsin 24,562
Colorado 24,250
Delaware 24,000
Arizona 21,556
Louisiana 18,650
Alabama 15,800
Kansas 14,000
Oklahoma 4,433
In [49]:
# The Average Number of Employee in each State.
# Join the Dataframe 'gdfsts' with 'dfstavremp'
gdfstsstavremp = gdfsts.merge(dfstavremp, how = 'inner', on = ['State'])
gdfstsstavremp.head(2)
Out[49]:
State region postal latitude longitude geometry Employees
0 Minnesota Midwest MN 46 -93 POLYGON ((-89.95766 47.28691, -90.13175 47.292... 74,700
1 Idaho West ID 44 -114 POLYGON ((-116.04823 49.00037, -115.9678 47.95... 122,300
In [50]:
mstavremp = gdfstsstavremp.explore(column='Employees', name='Average Number of Employee in each State', cmap='RdYlGn', edgecolor='black')
folium.LayerControl().add_to(mstavremp)
mstavremp
Out[50]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [51]:
# Check the Most Efficient Company in each State
# Efficient here means how big Revenue is produced by each Employee.
dfstmaxeffco = df.head(1)
dfstmaxeffco.insert(0, 'Efficiency', 1) # Add new Column 'Efficiency' to new

for st in stslist[0:]:
    dfst = df.where(df['State'] == st[0]).dropna()
    dfst['Efficiency'] = dfst['Revenue (rounded)']/dfst['Employees']
    dfst[['Zip Code']] = int(dfst['Zip Code'].iloc[0])
    dfstmaxeffco = pd.concat([dfstmaxeffco, dfst.sort_values(by='Efficiency',ascending=False).head(1)], ignore_index=True)
    
dfstmaxeffco = dfstmaxeffco.drop(0)
dfstmaxeffco[['State','City','Company','Industry','Zip Code','Efficiency']].sort_values(by='Efficiency', ascending=False).reset_index(drop=True)
Out[51]:
State City Company Industry Zip Code Efficiency
0 New York New York StoneX Diversified Financials 10017 22,200,000
1 California El Segundo A-Mark Precious Metals Wholesalers: Diversified 95014 19,400,000
2 District of Columbia Washington Fannie Mae Diversified Financials 20005 18,621,951
3 Virginia McLean Freddie Mac Diversified Financials 22102 15,074,074
4 Texas San Antonio Valero Energy Petroleum Refining 77389 12,525,253
5 Ohio Toledo Welltower Real Estate 43017 11,428,571
6 Florida Miami World Kinect Energy 33811 8,978,723
7 New Jersey Parsippany PBF Energy Petroleum Refining 8933 8,487,179
8 Oklahoma Oklahoma City Devon Energy Mining, Crude-Oil Production 74103 6,913,043
9 Pennsylvania Conshohocken Cencora Wholesalers: Health Care 19428 6,681,818
10 Tennessee Brentwood Delek US Petroleum Refining 38120 6,250,000
11 Colorado Denver Ovintiv Mining, Crude-Oil Production 80112 5,750,000
12 Missouri Chesterfield Reinsurance of America Insurance: Life, Health (Stock) 63105 5,390,244
13 Wisconsin Milwaukee Northwestern Mutual Insurance: Life, Health (Mutual) 53202 5,048,780
14 Massachusetts Waltham Global Partners Energy 1701 4,526,316
15 Minnesota Inver Grove Heights CHS Food Production 55344 3,672,897
16 Connecticut Bloomfield Cigna Health Care: Pharmacy and Other Services 6002 3,412,983
17 Arizona Scottsdale Taylor Morrison Home Homebuilders 85004 2,733,333
18 Georgia Atlanta Pulte Homebuilders 30339 2,632,353
19 Nebraska Omaha Mutual of Omaha Insurance Insurance: Life, Health (Mutual) 68131 2,246,154
20 Michigan Lansing Auto-Owners Insurance Insurance: Property and Casualty (Mutual) 48265 2,164,384
21 Illinois Chicago Archer Daniels Midland Food Production 60015 1,979,167
22 Rhode Island Johnston FM Insurance: Property and Casualty (Stock) 2895 1,793,103
23 Kentucky Louisville Humana Health Care: Insurance and Managed Care 40202 1,792,998
24 Indiana Indianapolis Elevance Health Health Care: Insurance and Managed Care 46204 1,706,847
25 Maryland Baltimore Constellation Energy Energy 20817 1,661,972
26 Arkansas El Dorado Murphy USA Specialty Retailers: Other 72712 1,543,103
27 North Carolina Charlotte Sonic Automotive Automotive Retailing, Services 28255 1,314,815
28 Oregon Medford Lithia Motors Automotive Retailing, Services 97005 1,211,921
29 Washington Bellevue Paccar Motor Vehicles & Parts 98109 1,119,601
30 Louisiana New Orleans Entergy Utilities: Gas and Electric 71203 967,480
31 Iowa Des Moines Principal Financial Insurance: Life, Health (Stock) 50392 817,259
32 Kansas Merriam Seaboard Food Production 66202 650,000
33 Alabama Birmingham Vulcan Materials Building Materials, Glass 35203 616,667
34 Idaho Boise Micron Technology Semiconductors and Other Electronic Components 83706 522,917
35 Delaware Wilmington DuPont Chemicals 19805 516,667
36 Nevada Las Vegas Las Vegas Sands Hotels, Casinos, Resorts 89109 281,796
In [52]:
# The Most Efficient Company in each State.
# Join the Dataframe 'gdfsts' with 'dfstmaxeffco'
gdfstsmaxeffco = gdfsts.merge(dfstmaxeffco, how = 'inner', on = ['State'])
gdfstsmaxeffco.head(2)
Out[52]:
State region postal latitude longitude geometry Efficiency Company Industry City Zip Code Website Employees Revenue (rounded) CEO
0 Minnesota Midwest MN 46 -93 POLYGON ((-89.95766 47.28691, -90.13175 47.292... 3,672,897 CHS Food Production Inver Grove Heights 55344 chsinc.com 10,700 39,300,000,000 Jay Debertin
1 Idaho West ID 44 -114 POLYGON ((-116.04823 49.00037, -115.9678 47.95... 522,917 Micron Technology Semiconductors and Other Electronic Components Boise 83706 micron.com 48,000 25,100,000,000 Sanjay Mehrotra
In [53]:
mstmaxeffco = gdfstsmaxeffco.explore(column='Efficiency', name='Most Efficient Company in each State', cmap='RdYlGn', edgecolor='black')
folium.LayerControl().add_to(mstmaxeffco)
mstmaxeffco
Out[53]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [54]:
# Check the Least Efficient Company in each State
dfstmineffco = df.head(1)
dfstmineffco.insert(0, 'Efficiency', 1) # Add new Column 'Efficiency' to new

for st in stslist[0:]:
    dfst = df.where(df['State'] == st[0]).dropna()
    dfst['Efficiency'] = dfst['Revenue (rounded)']/dfst['Employees']
    dfstmineffco = pd.concat([dfstmineffco, dfst.sort_values(by='Efficiency',ascending=True).head(1)], ignore_index=True)
    
dfstmineffco = dfstmineffco.drop(0)
dfstmineffco[['State','City','Company','Industry','Zip Code','Efficiency']].sort_values(by='Efficiency', ascending=False).reset_index(drop=True)
Out[54]:
State City Company Industry Zip Code Efficiency
0 Oklahoma Tulsa Williams Pipelines 74172 1,810,345
1 Kansas Merriam Seaboard Food Production 66202 650,000
2 Oregon Beaverton Nike Apparel 97005 647,355
3 Nebraska Omaha Peter Kiewit Sons' Engineering & Construction 68102 528,302
4 Louisiana Monroe Lumen Technologies Telecommunications 71203 524,000
5 Delaware Wilmington DuPont Chemicals 19805 516,667
6 Alabama Birmingham Regions Financial Commercial Banks 35203 479,592
7 Iowa Ankeny Casey's General Stores Specialty Retailers: Other 50021 450,151
8 Rhode Island Providence Textron Aerospace & Defense 02903 402,941
9 Idaho Boise Albertsons Food & Drug Stores 83706 402,848
10 District of Columbia Washington Xylem Industrial Machinery 20003 373,913
11 Arkansas Bentonville Walmart General Merchandisers 72712 324,286
12 Indiana Evansville Berry Global Packaging, Containers 47710 292,857
13 Wisconsin Menomonee Falls Kohl's General Merchandisers 53051 270,000
14 Georgia Atlanta UPS Mail, Package and Freight Delivery 30328 244,761
15 Minnesota Minneapolis Target General Merchandisers 55403 242,273
16 Kentucky Louisville Yum Brands Food Services 40213 236,593
17 Nevada Reno Caesars Entertainment Hotels, Casinos, Resorts 89501 226,000
18 Arizona Phoenix Sprouts Farmers Market Food & Drug Stores 85054 220,000
19 Ohio Cincinnati Cintas Diversified Outsourcing Services 45262 206,452
20 Missouri Springfield O'Reilly Automotive Specialty Retailers: Other 65802 195,093
21 Tennessee Memphis AutoZone Specialty Retailers: Other 38103 183,532
22 North Carolina Durham IQVIA s Health Care: Pharmacy and Other Services 27703 175,000
23 Illinois Chicago McDonald's Food Services 60607 172,667
24 Colorado Denver DaVita Health Care: Medical Facilities 80202 168,421
25 Maryland Bethesda Marriott International Hotels, Casinos, Resorts 20814 161,935
26 Massachusetts Framingham TJX Specialty Retailers: Apparel 01701 154,945
27 Michigan Southfield Lear Motor Vehicles & Parts 48033 134,139
28 Washington Seattle Starbucks Food Services 98134 100,277
29 Connecticut Greenwich GXO Logistics Transportation and Logistics 06831 91,051
30 New York New York ABM Industries Diversified Outsourcing Services 10006 71,795
31 Pennsylvania Philadelphia Aramark Diversified Outsourcing Services 19103 65,242
32 Virginia McLean Hilton Hotels, Casinos, Resorts 22102 61,878
33 Florida Orlando Darden Restaurants Food Services 32837 59,655
34 New Jersey Teaneck Cognizant Technology Information Technology Services 07666 58,492
35 Texas Plano Yum China s Food Services 75074 46,029
36 California Newark Concentrix Information Technology Services 94560 21,333
In [55]:
# Join the Dataframe 'gdfsts' with 'dfstmineffco'
gdfstsmineffco = gdfsts.merge(dfstmineffco, how = 'inner', on = ['State']).sort_values('Efficiency', ascending=False).reset_index(drop=True)
gdfstsmineffco.head(2)
Out[55]:
State region postal latitude longitude geometry Efficiency Company Industry City Zip Code Website Employees Revenue (rounded) CEO
0 Oklahoma South OK 35 -97 POLYGON ((-103.00322 36.99516, -102.04118 36.9... 1,810,345 Williams Pipelines Tulsa 74172 williams.com 5,800 10,500,000,000 Alan Armstrong
1 Kansas Midwest KS 38 -98 POLYGON ((-102.04118 36.99198, -102.04012 38.4... 650,000 Seaboard Food Production Merriam 66202 seaboardcorp.com 14,000 9,100,000,000 Robert Steer
In [56]:
mstmineffco = gdfstsmineffco.explore(column='Efficiency', name='Least Efficient Company in each State', cmap='RdYlGn', edgecolor='black')
folium.LayerControl().add_to(mstmineffco)
mstmineffco
Out[56]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [57]:
# Check the Average Efficiency in each State
dfstavreff = df.head(1)
dfstavreff.insert(0, 'Efficiency', 1) # Add new Column 'Efficiency' to new

for st in stslist[0:]:
    dfst = df.where(df['State'] == st[0]).dropna()
    dfst['Efficiency'] = dfst['Revenue (rounded)']/dfst['Employees']
    #print(dfct.groupby(['State','City'], as_index=False).mean('Efficiency'))
    dfstavreff = pd.concat([dfstavreff, dfst.groupby(['State'], as_index=False).mean('Efficiency')], ignore_index=True)[['State','Efficiency']]
    
dfstavreff = dfstavreff.drop(0)
dfstavreff.sort_values(by='Efficiency', ascending=False).reset_index(drop=True)
Out[57]:
State Efficiency
0 District of Columbia 6,460,449
1 Oklahoma 4,298,822
2 Texas 2,644,095
3 Ohio 1,818,979
4 New York 1,747,529
5 Missouri 1,495,312
6 California 1,459,801
7 Colorado 1,366,474
8 Virginia 1,332,278
9 Wisconsin 1,320,243
10 Massachusetts 1,273,417
11 New Jersey 1,182,423
12 Nebraska 1,116,963
13 Pennsylvania 1,115,642
14 Florida 1,107,382
15 Rhode Island 1,088,965
16 Minnesota 1,083,344
17 Connecticut 972,484
18 Tennessee 945,176
19 Oregon 929,638
20 Arizona 929,285
21 Michigan 862,969
22 Indiana 807,850
23 Maryland 803,561
24 Kentucky 778,332
25 Louisiana 745,740
26 Georgia 742,803
27 Illinois 731,582
28 North Carolina 654,844
29 Arkansas 653,435
30 Kansas 650,000
31 Iowa 633,705
32 Washington 561,945
33 Alabama 548,129
34 Delaware 516,667
35 Idaho 462,883
36 Nevada 252,357
In [58]:
# Join the Dataframe 'dfstavreff' with 'df'
gdfstsstavreff = gdfsts.merge(dfstavreff, how = 'inner', on = ['State'])
gdfstsstavreff = gdfstavreff.sort_values('Efficiency', ascending=False).reset_index(drop=True)
gdfstsstavreff
---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
Cell In[58], line 3
      1 # Join the Dataframe 'dfstavreff' with 'df'
      2 gdfstsstavreff = gdfsts.merge(dfstavreff, how = 'inner', on = ['State'])
----> 3 gdfstsstavreff = gdfstavreff.sort_values('Efficiency', ascending=False).reset_index(drop=True)
      4 gdfstsstavreff

NameError: name 'gdfstavreff' is not defined
In [ ]:
mstavreff = gdfstsstavreff.explore(column='Efficiency', name='The Average Efficiency in each State', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mstavreff)
mstavreff
In [ ]:
 

Statistics in City Level¶

In [158]:
# Grab all distinct City names
dfcts = df[['City','State']]
dfcts = dfcts.drop_duplicates()
dfcts = dfcts.sort_values('City', ascending=True).reset_index(drop=True)
ctslist = dfcts.to_numpy().tolist()
ctslist[1][0]

for cts in ctslist:
    print(cts[0], ',', cts[1])
    #print("---------------")
Abbott Park , Illinois
Akron , Ohio
Allentown , Pennsylvania
Ankeny , Iowa
Antioch , Tennessee
Arden Hills , Minnesota
Arlington , Virginia
Arlington , Texas
Armonk , New York
Ashburn , Virginia
Atlanta , Georgia
Auburn Hills , Michigan
Austin , Minnesota
Austin , Texas
Baltimore , Maryland
Beaverton , Oregon
Bellevue , Washington
Benton Harbor , Michigan
Bentonville , Arkansas
Bethesda , Maryland
Beverly Hills , California
Birmingham , Alabama
Bloomfield , Connecticut
Bloomfield Hills , Michigan
Bloomington , Illinois
Boise , Idaho
Bolingbrook , Illinois
Boston , Massachusetts
Brentwood , Tennessee
Buffalo , New York
Burbank , California
Burlington , Massachusetts
Burlington , New Jersey
Burlington , North Carolina
Byron Center , Michigan
Calhoun , Georgia
Cambridge , Massachusetts
Camden , New Jersey
Canonsburg , Pennsylvania
Centennial , Colorado
Chandler , Arizona
Charlotte , North Carolina
Chattanooga , Tennessee
Chesapeake , Virginia
Chesterfield , Missouri
Chicago , Illinois
Cincinnati , Ohio
Cleveland , Ohio
Columbus , Georgia
Columbus , Indiana
Columbus , Ohio
Conshohocken , Pennsylvania
Coral Gables , Florida
Coraopolis , Pennsylvania
Corning , New York
Corona , California
Cupertino , California
Dallas , Texas
Dearborn , Michigan
Deerfield , Illinois
Denver , Colorado
Des Moines , Iowa
Des Peres , Missouri
Detroit , Michigan
Downers Grove , Illinois
Dublin , Ohio
Dublin , California
Duluth , Georgia
Durham , North Carolina
Eden Prairie , Minnesota
El Dorado , Arkansas
El Segundo , California
Elkhart , Indiana
Englewood , Colorado
Erie , Pennsylvania
Estero , Florida
Evansville , Indiana
Evendale , Ohio
Fairfield , Ohio
Falls Church , Virginia
Farmington , Connecticut
Findlay , Ohio
Fort Lauderdale , Florida
Fort Washington , Pennsylvania
Fort Wayne , Indiana
Fort Worth , Texas
Foster City , California
Framingham , Massachusetts
Franklin , Tennessee
Franklin Lakes , New Jersey
Fremont , California
Glen Allen , Virginia
Glenview , Illinois
Goodlettsville , Tennessee
Greenwich , Connecticut
Hartford , Connecticut
Herndon , Virginia
Hershey , Pennsylvania
Houston , Texas
Indianapolis , Indiana
Inver Grove Heights , Minnesota
Irvine , California
Irving , Texas
Issaquah , Washington
Jackson , Michigan
Jacksonville , Florida
Johnston , Rhode Island
Juno Beach , Florida
King of Prussia , Pennsylvania
Kingsport , Tennessee
Lake Forest , Illinois
Lakeland , Florida
Lansing , Michigan
Las Vegas , Nevada
Livonia , Michigan
Long Beach , California
Long Island City , New York
Los Gatos , California
Louisville , Kentucky
Lowell , Arkansas
Madison , Wisconsin
Manhattan Beach , California
Maplewood , Minnesota
Marlborough , Massachusetts
Maumee , Ohio
Mayfield Village , Ohio
McLean , Virginia
Medford , Oregon
Melbourne , Florida
Melville , New York
Memphis , Tennessee
Menlo Park , California
Menomonee Falls , Wisconsin
Mentor , Ohio
Merriam , Kansas
Miami , Florida
Midland , Texas
Midland , Michigan
Milpitas , California
Milwaukee , Wisconsin
Minneapolis , Minnesota
Moline , Illinois
Monroe , Louisiana
Mooresville , North Carolina
Mountain View , California
Nashville , Tennessee
New Braunfels , Texas
New Britain , Connecticut
New Brunswick , New Jersey
New Orleans , Louisiana
New York , New York
Newark , California
Newark , New Jersey
Newport Beach , California
Newport News , Virginia
North Chicago , Illinois
Northbrook , Illinois
Norwalk , Connecticut
Oak Brook , Illinois
Oakland , California
Oklahoma City , Oklahoma
Omaha , Nebraska
Orlando , Florida
Orrville , Ohio
Oshkosh , Wisconsin
Palm Beach Gardens , Florida
Palo Alto , California
Parsippany , New Jersey
Philadelphia , Pennsylvania
Phoenix , Arizona
Pittsburgh , Pennsylvania
Plano , Texas
Plantation , Florida
Pleasanton , California
Portage , Michigan
Princeton , New Jersey
Providence , Rhode Island
Purchase , New York
Radnor , Pennsylvania
Rahway , New Jersey
Raleigh , North Carolina
Redmond , Washington
Redwood City , California
Reno , Nevada
Reston , Virginia
Richfield , Minnesota
Richmond , Virginia
Riverwoods , Illinois
Rolling Meadows , Illinois
Roseland , New Jersey
Rosemead , California
Rosemont , Illinois
Round Rock , Texas
San Antonio , Texas
San Diego , California
San Francisco , California
San Jose , California
San Mateo , California
Santa Clara , California
Scottsdale , Arizona
Seattle , Washington
Secaucus , New Jersey
Southfield , Michigan
Spring , Texas
Springdale , Arkansas
Springfield , Massachusetts
Springfield , Missouri
St. Louis , Missouri
St. Paul , Minnesota
St. Petersburg , Florida
Stamford , Connecticut
Summit , New Jersey
Sumner , Washington
Sunny Isles Beach , Florida
Sunnyvale , California
Tampa , Florida
Tarrytown , New York
Teaneck , New Jersey
Tempe , Arizona
Thousand Oaks , California
Toledo , Ohio
Tulsa , Oklahoma
Vernon Hills , Illinois
Victor , New York
Wallingford , Connecticut
Waltham , Massachusetts
Warsaw , Indiana
Washington , District of Columbia
Westchester , Illinois
Westerville , Ohio
Westlake , Texas
Westminster , Colorado
Wilmington , Delaware
Wilmington , Massachusetts
Winona , Minnesota
Woodland Hills , California
Woonsocket , Rhode Island
In [159]:
df.where(df['Zip Code'] == '44143').dropna()
Out[159]:
Company Industry City State Zip Code Website Employees Revenue (rounded) CEO
56 Progressive Insurance: Property and Casualty (Stock) Mayfield Village Ohio 44143 progressive.com 66,300 75,400,000,000 Susan Patricia Griffith
In [160]:
# Check the Largest Revenue Company in each City
dfmaxrevco = df.head(1)

for ct in ctslist[0:]:
    dfct = df.where(df['City'] == ct[0]).where(df['State'] == ct[1]).dropna()
    mnmaxrev = dfct['Revenue (rounded)'].max()
    dfctmaxrevco = dfct.where(dfct['Revenue (rounded)'] == mnmaxrev).dropna()
    dfmaxrevco = pd.concat([dfmaxrevco, dfctmaxrevco], ignore_index=True)
    
dfmaxrevco = dfmaxrevco.drop(0)
dfmaxrevco[['City','State','Company','Industry','Zip Code','Revenue (rounded)']].sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
Out[160]:
City State Company Industry Zip Code Revenue (rounded)
0 Bentonville Arkansas Walmart General Merchandisers 72712 681,000,000,000
1 Seattle Washington Amazon Internet Services and Retailing 98109 638,000,000,000
2 Eden Prairie Minnesota UnitedHealth Health Care: Insurance and Managed Care 55344 400,300,000,000
3 Cupertino California Apple Computers, Office Equipment 95014 391,000,000,000
4 Woonsocket Rhode Island CVS Health Health Care: Pharmacy and Other Services 02895 372,800,000,000
5 Omaha Nebraska Berkshire Hathaway Insurance: Property and Casualty (Stock) 68131 371,400,000,000
6 Mountain View California Alphabet Internet Services and Retailing 94043 350,000,000,000
7 Spring Texas Exxon Mobil Petroleum Refining 77389 349,600,000,000
8 Irving Texas McKesson Wholesalers: Health Care 75039 309,000,000,000
9 Conshohocken Pennsylvania Cencora Wholesalers: Health Care 19428 294,000,000,000
10 New York New York JPMorgan Chase Commercial Banks 10017 278,900,000,000
11 Issaquah Washington Costco General Merchandisers 98027 254,500,000,000
12 Bloomfield Connecticut Cigna Health Care: Pharmacy and Other Services 06002 247,100,000,000
13 Redmond Washington Microsoft Computer Software 98052 245,100,000,000
14 Dublin Ohio Cardinal Health Wholesalers: Health Care 43017 226,800,000,000
15 Houston Texas Chevron Petroleum Refining 77002 202,800,000,000
16 Charlotte North Carolina Bank of America Commercial Banks 28255 192,400,000,000
17 Detroit Michigan General Motors Motor Vehicles & Parts 48265 187,400,000,000
18 Dearborn Michigan Ford Motor Motor Vehicles & Parts 48126 185,000,000,000
19 Indianapolis Indiana Elevance Health Health Care: Insurance and Managed Care 46204 177,000,000,000
20 Menlo Park California Meta Internet Services and Retailing 94025 164,500,000,000
21 St. Louis Missouri Centene Health Care: Insurance and Managed Care 63105 163,100,000,000
22 Atlanta Georgia Home Depot Specialty Retailers: Other 30339 159,500,000,000
23 Washington District of Columbia Fannie Mae Diversified Financials 20005 152,700,000,000
24 Deerfield Illinois Walgreens Food & Drug Stores 60015 147,700,000,000
25 Cincinnati Ohio Kroger Food & Drug Stores 45202 147,100,000,000
26 Findlay Ohio Marathon Petroleum Petroleum Refining 45840 140,400,000,000
27 Santa Clara California Nvidia Semiconductors and Other Electronic Components 95051 130,500,000,000
28 San Francisco California Wells Fargo Commercial Banks 94104 125,400,000,000
29 San Antonio Texas Valero Energy Petroleum Refining 78249 124,000,000,000
30 Philadelphia Pennsylvania Comcast Telecommunications 19103 123,700,000,000
31 Bloomington Illinois State Farm Insurance: Property and Casualty (Mutual) 61710 123,000,000,000
32 Dallas Texas AT&T Telecommunications 75202 122,300,000,000
33 McLean Virginia Freddie Mac Diversified Financials 22102 122,100,000,000
34 Louisville Kentucky Humana Health Care: Insurance and Managed Care 40202 117,800,000,000
35 Minneapolis Minnesota Target General Merchandisers 55403 106,600,000,000
36 Austin Texas Tesla Motor Vehicles & Parts 78725 97,700,000,000
37 Round Rock Texas Dell Technologies Computers, Office Equipment 78682 95,600,000,000
38 Purchase New York PepsiCo Food Consumer Products 10577 91,900,000,000
39 Burbank California Walt Disney Entertainment 91521 91,400,000,000
40 New Brunswick New Jersey Johnson & Johnson Pharmaceuticals 08933 88,800,000,000
41 Memphis Tennessee FedEx Mail, Package and Freight Delivery 38120 87,700,000,000
42 Chicago Illinois Archer Daniels Midland Food Production 60601 85,500,000,000
43 Mooresville North Carolina Lowe's Specialty Retailers: Other 28117 83,700,000,000
44 Arlington Virginia RTX Aerospace & Defense 22209 80,700,000,000
45 Boise Idaho Albertsons Food & Drug Stores 83706 79,200,000,000
46 Mayfield Village Ohio Progressive Insurance: Property and Casualty (Stock) 44143 75,400,000,000
47 Bethesda Maryland Lockheed Martin Aerospace & Defense 20817 71,000,000,000
48 Nashville Tennessee HCA Healthcare Health Care: Medical Facilities 37203 70,600,000,000
49 Newark New Jersey Prudential Financial Insurance: Life, Health (Stock) 07102 70,400,000,000
50 Rahway New Jersey Merck Pharmaceuticals 07065 64,200,000,000
51 Northbrook Illinois Allstate Insurance: Property and Casualty (Stock) 60062 64,100,000,000
52 Armonk New York IBM Information Technology Services 10504 62,800,000,000
53 Lakeland Florida Publix Super Markets Food & Drug Stores 33811 60,200,000,000
54 Columbus Ohio Nationwide Insurance: Property and Casualty (Mutual) 43215 58,600,000,000
55 Fremont California TD Synnex Wholesalers: Electronics and Office Equipment 94538 58,500,000,000
56 Framingham Massachusetts TJX Specialty Retailers: Apparel 01701 56,400,000,000
57 North Chicago Illinois AbbVie Pharmaceuticals 60064 56,300,000,000
58 Stamford Connecticut Charter Communications Telecommunications 06902 55,100,000,000
59 Richmond Virginia Performance Food Wholesalers: Food and Grocery 23238 54,700,000,000
60 Fort Worth Texas American Airlines Airlines 76155 54,200,000,000
61 San Jose California Cisco Systems Network and Other Communications Equipment 95134 53,800,000,000
62 Palo Alto California HP Computers, Office Equipment 94304 53,600,000,000
63 Springdale Arkansas Tyson Foods Food Production 72762 53,300,000,000
64 Moline Illinois Deere Construction and Farm Machinery 61265 51,700,000,000
65 Beaverton Oregon Nike Apparel 97005 51,400,000,000
66 Boston Massachusetts Liberty Mutual Insurance Insurance: Property and Casualty (Stock) 02116 50,400,000,000
67 Princeton New Jersey Bristol-Myers Squibb Pharmaceuticals 08543 48,300,000,000
68 Irvine California Ingram Micro Wholesalers: Electronics and Office Equipment 92612 48,000,000,000
69 Reston Virginia General Dynamics Aerospace & Defense 20190 47,700,000,000
70 Springfield Massachusetts Mass Mutual Insurance: Life, Health (Mutual) 01111 43,100,000,000
71 Midland Michigan Dow Chemicals 48674 43,000,000,000
72 Waltham Massachusetts Thermo Fisher Scientific Scientific, Photographic and Control Equipment 02451 42,900,000,000
73 Miami Florida World Kinect Energy 33178 42,200,000,000
74 Abbott Park Illinois Abbott Laboratories Medical Products and Equipment 60064 42,000,000,000
75 Richfield Minnesota Best Buy Specialty Retailers: Other 55423 41,500,000,000
76 Milwaukee Wisconsin Northwestern Mutual Insurance: Life, Health (Mutual) 53202 41,400,000,000
77 Falls Church Virginia Northrop Grumman Aerospace & Defense 22042 41,000,000,000
78 Goodlettsville Tennessee Dollar General Specialty Retailers: Other 37072 40,600,000,000
79 Long Beach California Molina Healthcare Health Care: Insurance and Managed Care 90802 40,600,000,000
80 Inver Grove Heights Minnesota CHS Food Production 55077 39,300,000,000
81 Los Gatos California Netflix Entertainment 95032 39,000,000,000
82 San Diego California Qualcomm Semiconductors and Other Electronic Components 92121 39,000,000,000
83 Evendale Ohio General Electric Aerospace & Defense 45215 38,700,000,000
84 Rosemont Illinois US Foods Wholesalers: Food and Grocery 60018 37,900,000,000
85 Arlington Texas D.R. Horton Homebuilders 76011 36,800,000,000
86 Medford Oregon Lithia Motors Automotive Retailing, Services 97501 36,600,000,000
87 Cambridge Massachusetts GE Vernova Energy 02141 34,900,000,000
88 Pittsburgh Pennsylvania PNC Commercial Banks 15222 34,400,000,000
89 Columbus Indiana Cummins Industrial Machinery 47201 34,100,000,000
90 Bellevue Washington Paccar Motor Vehicles & Parts 98004 33,700,000,000
91 Thousand Oaks California Amgen Pharmaceuticals 91320 33,400,000,000
92 Parsippany New Jersey PBF Energy Petroleum Refining 07054 33,100,000,000
93 Jacksonville Florida GuideWell Mutual Insurance: Life, Health (Stock) 32246 33,000,000,000
94 Providence Rhode Island United Natural Foods Wholesalers: Food and Grocery 02908 31,000,000,000
95 Chesapeake Virginia Dollar Tree Specialty Retailers: Other 23320 30,800,000,000
96 Bloomfield Hills Michigan Penske Automotive Automotive Retailing, Services 48302 30,500,000,000
97 Newport News Virginia Ferguson Wholesalers: Diversified 23606 29,600,000,000
98 St. Petersburg Florida Jabil Semiconductors and Other Electronic Components 33716 28,900,000,000
99 Foster City California Gilead Sciences Pharmaceuticals 94404 28,800,000,000
100 Centennial Colorado Arrow Electronics Wholesalers: Electronics and Office Equipment 80112 27,900,000,000
101 Fort Lauderdale Florida AutoNation Automotive Retailing, Services 33301 26,800,000,000
102 Hartford Connecticut Hartford Insurance Insurance: Property and Casualty (Stock) 06155 26,500,000,000
103 Westlake Texas Charles Schwab Securities 76262 26,000,000,000
104 Phoenix Arizona Freeport-McMoRan Mining, Crude-Oil Production 85004 25,500,000,000
105 Juno Beach Florida NextEra Energy Utilities: Gas and Electric 33408 24,800,000,000
106 Palm Beach Gardens Florida Carrier Global Industrial Machinery 33418 24,800,000,000
107 St. Paul Minnesota 3M Chemicals 55144 24,600,000,000
108 Oakland California PG&E Utilities: Gas and Electric 94612 24,400,000,000
109 Norwalk Connecticut Booking s Internet Services and Retailing 06854 23,700,000,000
110 Baltimore Maryland Constellation Energy Energy 21231 23,600,000,000
111 Riverwoods Illinois Discover Financial Diversified Financials 60015 23,600,000,000
112 Southfield Michigan Lear Motor Vehicles & Parts 48033 23,300,000,000
113 Beverly Hills California Live Nation Entertainment Entertainment 90210 23,200,000,000
114 Cleveland Ohio Sherwin-Williams Chemicals 44115 23,100,000,000
115 Portage Michigan Stryker Medical Products and Equipment 49002 22,600,000,000
116 Chesterfield Missouri Reinsurance of America Insurance: Life, Health (Stock) 63017 22,100,000,000
117 Tulsa Oklahoma Oneok Pipelines 74103 21,700,000,000
118 Melbourne Florida L3Harris Technologies Aerospace & Defense 32919 21,300,000,000
119 Madison Wisconsin American Family Insurance Insurance: Property and Casualty (Stock) 53783 21,300,000,000
120 Dublin California Ross Stores Specialty Retailers: Apparel 94568 21,100,000,000
121 Vernon Hills Illinois CDW Information Technology Services 60061 21,000,000,000
122 Marlborough Massachusetts BJ's Wholesale Club General Merchandisers 01752 20,500,000,000
123 Franklin Lakes New Jersey Becton Dickinson Medical Products and Equipment 07417 20,200,000,000
124 Teaneck New Jersey Cognizant Technology Information Technology Services 07666 19,700,000,000
125 Roseland New Jersey Automatic Data Processing Diversified Outsourcing Services 07068 19,200,000,000
126 Akron Ohio Goodyear Tire & Rubber Motor Vehicles & Parts 44316 18,900,000,000
127 Columbus Georgia Aflac Insurance: Life, Health (Stock) 31999 18,900,000,000
128 Denver Colorado Newmont Mining, Crude-Oil Production 80237 18,700,000,000
129 Radnor Pennsylvania Lincoln National Insurance: Life, Health (Stock) 19087 18,400,000,000
130 El Dorado Arkansas Murphy USA Specialty Retailers: Other 71730 17,900,000,000
131 Rosemead California Edison International Utilities: Gas and Electric 91770 17,600,000,000
132 Fort Wayne Indiana Steel Dynamics Metals 46804 17,500,000,000
133 Las Vegas Nevada MGM Resorts International Hotels, Casinos, Resorts 89109 17,200,000,000
134 Lake Forest Illinois W.W. Grainger Wholesalers: Diversified 60045 17,200,000,000
135 Duluth Georgia Asbury Automotive Automotive Retailing, Services 30097 17,200,000,000
136 Springfield Missouri O'Reilly Automotive Specialty Retailers: Other 65802 16,700,000,000
137 Glen Allen Virginia Markel Insurance: Property and Casualty (Stock) 23060 16,600,000,000
138 Benton Harbor Michigan Whirlpool Electronics, Electrical Equip. 49022 16,600,000,000
139 Des Peres Missouri Edward Jones Securities 63131 16,300,000,000
140 Menomonee Falls Wisconsin Kohl's General Merchandisers 53051 16,200,000,000
141 Arden Hills Minnesota Land O'Lakes Food Consumer Products 55126 16,200,000,000
142 Des Moines Iowa Principal Financial Insurance: Life, Health (Stock) 50392 16,100,000,000
143 Glenview Illinois Illinois Tool Works Industrial Machinery 60025 15,900,000,000
144 Oklahoma City Oklahoma Devon Energy Mining, Crude-Oil Production 73102 15,900,000,000
145 Lansing Michigan Auto-Owners Insurance Insurance: Property and Casualty (Mutual) 48917 15,800,000,000
146 King of Prussia Pennsylvania Universal Health Services Health Care: Medical Facilities 19406 15,800,000,000
147 Englewood Colorado EchoStar Telecommunications 80112 15,800,000,000
148 Newport Beach California Pacific Life Insurance: Life, Health (Stock) 92660 15,800,000,000
149 Summit New Jersey Kenvue Household and Personal Products 07901 15,500,000,000
150 Woodland Hills California Farmers Insurance Exchange Insurance: Property and Casualty (Mutual) 91367 15,500,000,000
151 Burlington Massachusetts Keurig Dr Pepper Beverages 01803 15,400,000,000
152 Durham North Carolina IQVIA s Health Care: Pharmacy and Other Services 27703 15,400,000,000
153 New Britain Connecticut Stanley Black & Decker Industrial Machinery 06053 15,400,000,000
154 Wallingford Connecticut Amphenol Network and Other Communications Equipment 06492 15,200,000,000
155 Raleigh North Carolina First Citizens BancShares Commercial Banks 27609 15,000,000,000
156 Brentwood Tennessee Tractor Supply Specialty Retailers: Other 37027 14,900,000,000
157 Ankeny Iowa Casey's General Stores Specialty Retailers: Other 50021 14,900,000,000
158 Canonsburg Pennsylvania Viatris Pharmaceuticals 15317 14,700,000,000
159 Antioch Tennessee LKQ Wholesalers: Diversified 37013 14,400,000,000
160 Farmington Connecticut Otis Worldwide Industrial Machinery 06032 14,300,000,000
161 Tarrytown New York Regeneron Pharmaceuticals Pharmaceuticals 10591 14,200,000,000
162 Auburn Hills Michigan BorgWarner Motor Vehicles & Parts 48326 14,100,000,000
163 Scottsdale Arizona Reliance Metals 85254 13,800,000,000
164 Tempe Arizona Carvana Automotive Retailing, Services 85281 13,700,000,000
165 Ashburn Virginia DXC Technology Information Technology Services 20147 13,700,000,000
166 Greenwich Connecticut W.R. Berkley Insurance: Property and Casualty (Stock) 06830 13,600,000,000
167 Buffalo New York M&T Bank Commercial Banks 14203 13,500,000,000
168 Coraopolis Pennsylvania Dick's Sporting Goods Specialty Retailers: Other 15108 13,400,000,000
169 Erie Pennsylvania Erie Insurance Insurance: Property and Casualty (Mutual) 16530 13,200,000,000
170 Monroe Louisiana Lumen Technologies Telecommunications 71203 13,100,000,000
171 Corning New York Corning Electronics, Electrical Equip. 14831 13,100,000,000
172 Burlington North Carolina Labcorp s Health Care: Pharmacy and Other Services 27215 13,000,000,000
173 Chattanooga Tennessee Unum Insurance: Life, Health (Stock) 37402 12,900,000,000
174 Melville New York Henry Schein Wholesalers: Health Care 11747 12,700,000,000
175 Franklin Tennessee Community Health Systems Health Care: Medical Facilities 37067 12,600,000,000
176 Coral Gables Florida Ryder System Transportation and Logistics 33134 12,600,000,000
177 Wilmington Delaware DuPont Chemicals 19805 12,400,000,000
178 Evansville Indiana Berry Global Packaging, Containers 47710 12,300,000,000
179 Westminster Colorado Ball Packaging, Containers 80021 12,100,000,000
180 Allentown Pennsylvania Air Products & Chemicals Chemicals 18106 12,100,000,000
181 Lowell Arkansas J.B. Hunt Transport Services Trucking, Truck Leasing 72745 12,100,000,000
182 Plantation Florida Chewy Internet Services and Retailing 33322 11,900,000,000
183 New Orleans Louisiana Entergy Utilities: Gas and Electric 70113 11,900,000,000
184 Austin Minnesota Hormel Foods Food Consumer Products 55912 11,900,000,000
185 Tampa Florida Crown s Packaging, Containers 33637 11,800,000,000
186 Rolling Meadows Illinois Arthur J. Gallagher Diversified Financials 60008 11,600,000,000
187 Orlando Florida Darden Restaurants Food Services 32837 11,400,000,000
188 Maumee Ohio Andersons Food Production 43537 11,300,000,000
189 Reno Nevada Caesars Entertainment Hotels, Casinos, Resorts 89501 11,300,000,000
190 Fairfield Ohio Cincinnati Financial Insurance: Property and Casualty (Stock) 45014 11,300,000,000
191 Plano Texas Yum China s Food Services 75074 11,300,000,000
192 Bolingbrook Illinois Ulta Beauty Specialty Retailers: Other 60440 11,300,000,000
193 Hershey Pennsylvania Hershey Food Consumer Products 17033 11,200,000,000
194 Midland Texas Diamondback Energy Mining, Crude-Oil Production 79701 11,100,000,000
195 Toledo Ohio Owens Corning Building Materials, Glass 43659 11,000,000,000
196 Calhoun Georgia Mohawk Industries Home Equipment, Furnishings 30701 10,800,000,000
197 Fort Washington Pennsylvania Toll Brothers Homebuilders 19034 10,800,000,000
198 Oshkosh Wisconsin Oshkosh Construction and Farm Machinery 54902 10,700,000,000
199 Burlington New Jersey Burlington Stores Specialty Retailers: Apparel 08016 10,600,000,000
200 Sumner Washington Lululemon athletica Specialty Retailers: Apparel 98390 10,600,000,000
201 Johnston Rhode Island FM Insurance: Property and Casualty (Stock) 02919 10,400,000,000
202 Victor New York Constellation Brands Beverages 14564 10,000,000,000
203 Sunny Isles Beach Florida Icahn Enterprises Diversified Financials 33160 10,000,000,000
204 Elkhart Indiana THOR Industries Motor Vehicles & Parts 46514 10,000,000,000
205 Secaucus New Jersey Quest Diagnostics Health Care: Pharmacy and Other Services 07094 9,900,000,000
206 Herndon Virginia QXO Building Products Wholesalers: Diversified 20170 9,800,000,000
207 Milpitas California KLA Semiconductors and Other Electronic Components 95035 9,800,000,000
208 El Segundo California A-Mark Precious Metals Wholesalers: Diversified 90245 9,700,000,000
209 Camden New Jersey Campbell's Food Consumer Products 08103 9,600,000,000
210 Newark California Concentrix Information Technology Services 94560 9,600,000,000
211 Byron Center Michigan SpartanNash Wholesalers: Food and Grocery 49315 9,500,000,000
212 Oak Brook Illinois Ace Hardware Wholesalers: Diversified 60523 9,500,000,000
213 Wilmington Massachusetts Analog Devices Semiconductors and Other Electronic Components 01887 9,400,000,000
214 Kingsport Tennessee Eastman Chemical Chemicals 37660 9,400,000,000
215 Birmingham Alabama Regions Financial Commercial Banks 35203 9,400,000,000
216 Long Island City New York JetBlue Airways Airlines 11101 9,300,000,000
217 Merriam Kansas Seaboard Food Production 66202 9,100,000,000
218 Manhattan Beach California Skechers U.S.A. Apparel 90266 9,000,000,000
219 Estero Florida Hertz Automotive Retailing, Services 33928 9,000,000,000
220 Mentor Ohio Avery Dennison Packaging, Containers 44060 8,800,000,000
221 Chandler Arizona Insight Enterprises Information Technology Services 85286 8,700,000,000
222 Redwood City California Equinix Real Estate 94065 8,700,000,000
223 San Mateo California Franklin Resources Securities 94403 8,500,000,000
224 Pleasanton California Workday Computer Software 94588 8,400,000,000
225 Sunnyvale California Intuitive Surgical Medical Products and Equipment 94086 8,400,000,000
226 Downers Grove Illinois Dover Industrial Machinery 60515 8,400,000,000
227 Maplewood Minnesota Solventum Medical Products and Equipment 55144 8,300,000,000
228 Orrville Ohio J.M. Smucker Food Consumer Products 44667 8,200,000,000
229 Westerville Ohio Vertiv s Electronics, Electrical Equip. 43082 8,000,000,000
230 Livonia Michigan Masco Home Equipment, Furnishings 48152 7,800,000,000
231 New Braunfels Texas Rush Enterprises Automotive Retailing, Services 78130 7,800,000,000
232 Warsaw Indiana Zimmer Biomet s Medical Products and Equipment 46580 7,700,000,000
233 Corona California Monster Beverage Beverages 92879 7,500,000,000
234 Winona Minnesota Fastenal Wholesalers: Diversified 55987 7,500,000,000
235 Jackson Michigan CMS Energy Utilities: Gas and Electric 49201 7,500,000,000
236 Westchester Illinois Ingredion Food Production 60154 7,400,000,000
In [161]:
# Join the Dataframe 'gdfusact' with 'dfmaxrevco' for the Top 10
gdfusactmaxrevco = gdfusact.merge(dfmaxrevco, how = 'inner', on = ['Zip Code'])
gdfusactmaxrevco = gdfusactmaxrevco.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [162]:
mctmaxrevco = gdfusactmaxrevco.explore(column='Revenue (rounded)', name='Biggest Revenue Company in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctmaxrevco)
mctmaxrevco
Out[162]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [163]:
# Check the Smallest Revenue Company in each City
dfminrevco = df.head(1)

for ct in ctslist[0:]:
    dfct = df.where(df['City'] == ct[0]).where(df['State'] == ct[1]).dropna()
    mnminrev = dfct['Revenue (rounded)'].min()
    dfctminrevco = dfct.where(dfct['Revenue (rounded)'] == mnminrev).dropna()
    dfminrevco = pd.concat([dfminrevco, dfctminrevco], ignore_index=True)
    
dfminrevco = dfminrevco.drop(0)
dfminrevco[['City','State','Company','Industry','Zip Code','Revenue (rounded)']].sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
Out[163]:
City State Company Industry Zip Code Revenue (rounded)
0 Bentonville Arkansas Walmart General Merchandisers 72712 681,000,000,000
1 Cupertino California Apple Computers, Office Equipment 95014 391,000,000,000
2 Woonsocket Rhode Island CVS Health Health Care: Pharmacy and Other Services 02895 372,800,000,000
3 Conshohocken Pennsylvania Cencora Wholesalers: Health Care 19428 294,000,000,000
4 Issaquah Washington Costco General Merchandisers 98027 254,500,000,000
5 Bloomfield Connecticut Cigna Health Care: Pharmacy and Other Services 06002 247,100,000,000
6 Redmond Washington Microsoft Computer Software 98052 245,100,000,000
7 Dublin Ohio Cardinal Health Wholesalers: Health Care 43017 226,800,000,000
8 Dearborn Michigan Ford Motor Motor Vehicles & Parts 48126 185,000,000,000
9 Menlo Park California Meta Internet Services and Retailing 94025 164,500,000,000
10 Findlay Ohio Marathon Petroleum Petroleum Refining 45840 140,400,000,000
11 Bloomington Illinois State Farm Insurance: Property and Casualty (Mutual) 61710 123,000,000,000
12 Round Rock Texas Dell Technologies Computers, Office Equipment 78682 95,600,000,000
13 Burbank California Walt Disney Entertainment 91521 91,400,000,000
14 New Brunswick New Jersey Johnson & Johnson Pharmaceuticals 08933 88,800,000,000
15 Mooresville North Carolina Lowe's Specialty Retailers: Other 28117 83,700,000,000
16 Mayfield Village Ohio Progressive Insurance: Property and Casualty (Stock) 44143 75,400,000,000
17 Nashville Tennessee HCA Healthcare Health Care: Medical Facilities 37203 70,600,000,000
18 Rahway New Jersey Merck Pharmaceuticals 07065 64,200,000,000
19 Northbrook Illinois Allstate Insurance: Property and Casualty (Stock) 60062 64,100,000,000
20 Armonk New York IBM Information Technology Services 10504 62,800,000,000
21 Lakeland Florida Publix Super Markets Food & Drug Stores 33811 60,200,000,000
22 Framingham Massachusetts TJX Specialty Retailers: Apparel 01701 56,400,000,000
23 North Chicago Illinois AbbVie Pharmaceuticals 60064 56,300,000,000
24 Fort Worth Texas American Airlines Airlines 76155 54,200,000,000
25 Springdale Arkansas Tyson Foods Food Production 72762 53,300,000,000
26 Austin Texas Oracle Computer Software 78741 53,000,000,000
27 Palo Alto California Broadcom Semiconductors and Other Electronic Components 94304 52,400,000,000
28 Moline Illinois Deere Construction and Farm Machinery 61265 51,700,000,000
29 Beaverton Oregon Nike Apparel 97005 51,400,000,000
30 San Antonio Texas USAA Insurance: Property and Casualty (Stock) 78288 48,600,000,000
31 Princeton New Jersey Bristol-Myers Squibb Pharmaceuticals 08543 48,300,000,000
32 Irvine California Ingram Micro Wholesalers: Electronics and Office Equipment 92612 48,000,000,000
33 Midland Michigan Dow Chemicals 48674 43,000,000,000
34 Abbott Park Illinois Abbott Laboratories Medical Products and Equipment 60064 42,000,000,000
35 Richfield Minnesota Best Buy Specialty Retailers: Other 55423 41,500,000,000
36 Falls Church Virginia Northrop Grumman Aerospace & Defense 22042 41,000,000,000
37 Long Beach California Molina Healthcare Health Care: Insurance and Managed Care 90802 40,600,000,000
38 Goodlettsville Tennessee Dollar General Specialty Retailers: Other 37072 40,600,000,000
39 Inver Grove Heights Minnesota CHS Food Production 55077 39,300,000,000
40 Los Gatos California Netflix Entertainment 95032 39,000,000,000
41 Evendale Ohio General Electric Aerospace & Defense 45215 38,700,000,000
42 Rosemont Illinois US Foods Wholesalers: Food and Grocery 60018 37,900,000,000
43 Arlington Texas D.R. Horton Homebuilders 76011 36,800,000,000
44 Medford Oregon Lithia Motors Automotive Retailing, Services 97501 36,600,000,000
45 Columbus Indiana Cummins Industrial Machinery 47201 34,100,000,000
46 Thousand Oaks California Amgen Pharmaceuticals 91320 33,400,000,000
47 Chesapeake Virginia Dollar Tree Specialty Retailers: Other 23320 30,800,000,000
48 Bloomfield Hills Michigan Penske Automotive Automotive Retailing, Services 48302 30,500,000,000
49 Spring Texas Hewlett Packard Computers, Office Equipment 77389 30,100,000,000
50 Foster City California Gilead Sciences Pharmaceuticals 94404 28,800,000,000
51 Purchase New York Mastercard Financial Data Services 10577 28,200,000,000
52 Centennial Colorado Arrow Electronics Wholesalers: Electronics and Office Equipment 80112 27,900,000,000
53 Fort Lauderdale Florida AutoNation Automotive Retailing, Services 33301 26,800,000,000
54 Hartford Connecticut Hartford Insurance Insurance: Property and Casualty (Stock) 06155 26,500,000,000
55 Westlake Texas Charles Schwab Securities 76262 26,000,000,000
56 Boise Idaho Micron Technology Semiconductors and Other Electronic Components 83716 25,100,000,000
57 Bethesda Maryland Marriott International Hotels, Casinos, Resorts 20814 25,100,000,000
58 Palm Beach Gardens Florida Carrier Global Industrial Machinery 33418 24,800,000,000
59 Juno Beach Florida NextEra Energy Utilities: Gas and Electric 33408 24,800,000,000
60 Oakland California Block Financial Data Services 94612 24,100,000,000
61 Riverwoods Illinois Discover Financial Diversified Financials 60015 23,600,000,000
62 Baltimore Maryland Constellation Energy Energy 21231 23,600,000,000
63 Southfield Michigan Lear Motor Vehicles & Parts 48033 23,300,000,000
64 Portage Michigan Stryker Medical Products and Equipment 49002 22,600,000,000
65 Chesterfield Missouri Reinsurance of America Insurance: Life, Health (Stock) 63017 22,100,000,000
66 Melbourne Florida L3Harris Technologies Aerospace & Defense 32919 21,300,000,000
67 Madison Wisconsin American Family Insurance Insurance: Property and Casualty (Stock) 53783 21,300,000,000
68 Dublin California Ross Stores Specialty Retailers: Apparel 94568 21,100,000,000
69 Vernon Hills Illinois CDW Information Technology Services 60061 21,000,000,000
70 Franklin Lakes New Jersey Becton Dickinson Medical Products and Equipment 07417 20,200,000,000
71 Teaneck New Jersey Cognizant Technology Information Technology Services 07666 19,700,000,000
72 Roseland New Jersey Automatic Data Processing Diversified Outsourcing Services 07068 19,200,000,000
73 Columbus Georgia Aflac Insurance: Life, Health (Stock) 31999 18,900,000,000
74 Memphis Tennessee AutoZone Specialty Retailers: Other 38103 18,500,000,000
75 Radnor Pennsylvania Lincoln National Insurance: Life, Health (Stock) 19087 18,400,000,000
76 El Dorado Arkansas Murphy USA Specialty Retailers: Other 71730 17,900,000,000
77 Eden Prairie Minnesota C.H. Robinson Worldwide Transportation and Logistics 55347 17,700,000,000
78 Rosemead California Edison International Utilities: Gas and Electric 91770 17,600,000,000
79 Fort Wayne Indiana Steel Dynamics Metals 46804 17,500,000,000
80 Philadelphia Pennsylvania Aramark Diversified Outsourcing Services 19103 17,400,000,000
81 Waltham Massachusetts Global Partners Energy 02453 17,200,000,000
82 Indianapolis Indiana Corteva Food Production 46268 16,900,000,000
83 Springfield Missouri O'Reilly Automotive Specialty Retailers: Other 65802 16,700,000,000
84 Marlborough Massachusetts Boston Scientific Medical Products and Equipment 01752 16,700,000,000
85 Benton Harbor Michigan Whirlpool Electronics, Electrical Equip. 49022 16,600,000,000
86 Mountain View California Intuit Computer Software 94043 16,300,000,000
87 Des Peres Missouri Edward Jones Securities 63131 16,300,000,000
88 Arden Hills Minnesota Land O'Lakes Food Consumer Products 55126 16,200,000,000
89 Menomonee Falls Wisconsin Kohl's General Merchandisers 53051 16,200,000,000
90 Des Moines Iowa Principal Financial Insurance: Life, Health (Stock) 50392 16,100,000,000
91 Oklahoma City Oklahoma Devon Energy Mining, Crude-Oil Production 73102 15,900,000,000
92 Glenview Illinois Illinois Tool Works Industrial Machinery 60025 15,900,000,000
93 Lansing Michigan Auto-Owners Insurance Insurance: Property and Casualty (Mutual) 48917 15,800,000,000
94 King of Prussia Pennsylvania Universal Health Services Health Care: Medical Facilities 19406 15,800,000,000
95 Dallas Texas Texas Instruments Semiconductors and Other Electronic Components 75243 15,600,000,000
96 Woodland Hills California Farmers Insurance Exchange Insurance: Property and Casualty (Mutual) 91367 15,500,000,000
97 Summit New Jersey Kenvue Household and Personal Products 07901 15,500,000,000
98 Durham North Carolina IQVIA s Health Care: Pharmacy and Other Services 27703 15,400,000,000
99 New Britain Connecticut Stanley Black & Decker Industrial Machinery 06053 15,400,000,000
100 Burlington Massachusetts Keurig Dr Pepper Beverages 01803 15,400,000,000
101 Stamford Connecticut United Rentals Specialty Retailers: Other 06902 15,300,000,000
102 Wallingford Connecticut Amphenol Network and Other Communications Equipment 06492 15,200,000,000
103 Deerfield Illinois Baxter International Medical Products and Equipment 60015 15,100,000,000
104 St. Petersburg Florida Raymond James Financial Securities 33716 14,900,000,000
105 Ankeny Iowa Casey's General Stores Specialty Retailers: Other 50021 14,900,000,000
106 Fremont California Lam Research Semiconductors and Other Electronic Components 94538 14,900,000,000
107 Canonsburg Pennsylvania Viatris Pharmaceuticals 15317 14,700,000,000
108 Norwalk Connecticut EMCOR Engineering & Construction 06851 14,600,000,000
109 Omaha Nebraska Mutual of Omaha Insurance Insurance: Life, Health (Mutual) 68175 14,600,000,000
110 Antioch Tennessee LKQ Wholesalers: Diversified 37013 14,400,000,000
111 Farmington Connecticut Otis Worldwide Industrial Machinery 06032 14,300,000,000
112 Charlotte North Carolina Sonic Automotive Automotive Retailing, Services 28211 14,200,000,000
113 Tarrytown New York Regeneron Pharmaceuticals Pharmaceuticals 10591 14,200,000,000
114 Ashburn Virginia DXC Technology Information Technology Services 20147 13,700,000,000
115 Tempe Arizona Carvana Automotive Retailing, Services 85281 13,700,000,000
116 Buffalo New York M&T Bank Commercial Banks 14203 13,500,000,000
117 Coraopolis Pennsylvania Dick's Sporting Goods Specialty Retailers: Other 15108 13,400,000,000
118 Erie Pennsylvania Erie Insurance Insurance: Property and Casualty (Mutual) 16530 13,200,000,000
119 Monroe Louisiana Lumen Technologies Telecommunications 71203 13,100,000,000
120 Corning New York Corning Electronics, Electrical Equip. 14831 13,100,000,000
121 Akron Ohio FirstEnergy Utilities: Gas and Electric 44308 13,000,000,000
122 Burlington North Carolina Labcorp s Health Care: Pharmacy and Other Services 27215 13,000,000,000
123 Chattanooga Tennessee Unum Insurance: Life, Health (Stock) 37402 12,900,000,000
124 Melville New York Henry Schein Wholesalers: Health Care 11747 12,700,000,000
125 Franklin Tennessee Community Health Systems Health Care: Medical Facilities 37067 12,600,000,000
126 Brentwood Tennessee Delek US Petroleum Refining 37027 12,500,000,000
127 Detroit Michigan DTE Energy Utilities: Gas and Electric 48226 12,500,000,000
128 Wilmington Delaware DuPont Chemicals 19805 12,400,000,000
129 Providence Rhode Island Citizens Financial Commercial Banks 02903 12,400,000,000
130 San Diego California LPL Financial s Securities 92121 12,400,000,000
131 Evansville Indiana Berry Global Packaging, Containers 47710 12,300,000,000
132 Arlington Virginia AES Utilities: Gas and Electric 22203 12,300,000,000
133 Coral Gables Florida MasTec Engineering & Construction 33134 12,300,000,000
134 Lowell Arkansas J.B. Hunt Transport Services Trucking, Truck Leasing 72745 12,100,000,000
135 Westminster Colorado Ball Packaging, Containers 80021 12,100,000,000
136 Columbus Ohio Huntington Bancshares Commercial Banks 43287 12,000,000,000
137 Plantation Florida Chewy Internet Services and Retailing 33322 11,900,000,000
138 Springfield Massachusetts Eversource Energy Utilities: Gas and Electric 01104 11,900,000,000
139 New Orleans Louisiana Entergy Utilities: Gas and Electric 70113 11,900,000,000
140 Austin Minnesota Hormel Foods Food Consumer Products 55912 11,900,000,000
141 Seattle Washington Alaska Air Airlines 98188 11,700,000,000
142 Duluth Georgia AGCO Construction and Farm Machinery 30096 11,700,000,000
143 Rolling Meadows Illinois Arthur J. Gallagher Diversified Financials 60008 11,600,000,000
144 Newport News Virginia Huntington Ingalls Industries Aerospace & Defense 23607 11,500,000,000
145 Orlando Florida Darden Restaurants Food Services 32837 11,400,000,000
146 Newport Beach California Chipotle Mexican Grill Food Services 92660 11,300,000,000
147 Bolingbrook Illinois Ulta Beauty Specialty Retailers: Other 60440 11,300,000,000
148 Las Vegas Nevada Las Vegas Sands Hotels, Casinos, Resorts 89113 11,300,000,000
149 Plano Texas Yum China s Food Services 75074 11,300,000,000
150 Reno Nevada Caesars Entertainment Hotels, Casinos, Resorts 89501 11,300,000,000
151 Fairfield Ohio Cincinnati Financial Insurance: Property and Casualty (Stock) 45014 11,300,000,000
152 Hershey Pennsylvania Hershey Food Consumer Products 17033 11,200,000,000
153 Midland Texas Diamondback Energy Mining, Crude-Oil Production 79701 11,100,000,000
154 Tampa Florida Mosaic Chemicals 33602 11,100,000,000
155 Boston Massachusetts Vertex Pharmaceuticals Pharmaceuticals 02210 11,000,000,000
156 Boston Massachusetts American Tower Real Estate 02116 11,000,000,000
157 Minneapolis Minnesota Thrivent Financial for Lutherans Insurance: Life, Health (Mutual) 55415 10,900,000,000
158 Raleigh North Carolina Advance Auto Parts Specialty Retailers: Other 27609 10,900,000,000
159 Calhoun Georgia Mohawk Industries Home Equipment, Furnishings 30701 10,800,000,000
160 Fort Washington Pennsylvania Toll Brothers Homebuilders 19034 10,800,000,000
161 Glen Allen Virginia Owens & Minor Wholesalers: Health Care 23060 10,700,000,000
162 McLean Virginia Booz Allen Hamilton Information Technology Services 22102 10,700,000,000
163 Oshkosh Wisconsin Oshkosh Construction and Farm Machinery 54902 10,700,000,000
164 Burlington New Jersey Burlington Stores Specialty Retailers: Apparel 08016 10,600,000,000
165 Bellevue Washington Expeditors International of Washington Transportation and Logistics 98006 10,600,000,000
166 Sumner Washington Lululemon athletica Specialty Retailers: Apparel 98390 10,600,000,000
167 Tulsa Oklahoma Williams Pipelines 74172 10,500,000,000
168 Jacksonville Florida Fidelity National Information Financial Data Services 32202 10,500,000,000
169 Auburn Hills Michigan Autoliv Motor Vehicles & Parts 48326 10,400,000,000
170 Johnston Rhode Island FM Insurance: Property and Casualty (Stock) 02919 10,400,000,000
171 Newark New Jersey Public Service Enterprise Utilities: Gas and Electric 07102 10,300,000,000
172 Maumee Ohio Dana Motor Vehicles & Parts 43537 10,300,000,000
173 Victor New York Constellation Brands Beverages 14564 10,000,000,000
174 Elkhart Indiana THOR Industries Motor Vehicles & Parts 46514 10,000,000,000
175 Englewood Colorado QVC Internet Services and Retailing 80112 10,000,000,000
176 Sunny Isles Beach Florida Icahn Enterprises Diversified Financials 33160 10,000,000,000
177 Secaucus New Jersey Quest Diagnostics Health Care: Pharmacy and Other Services 07094 9,900,000,000
178 Herndon Virginia QXO Building Products Wholesalers: Diversified 20170 9,800,000,000
179 Milpitas California KLA Semiconductors and Other Electronic Components 95035 9,800,000,000
180 El Segundo California A-Mark Precious Metals Wholesalers: Diversified 90245 9,700,000,000
181 Cambridge Massachusetts Biogen Pharmaceuticals 02142 9,700,000,000
182 Newark California Concentrix Information Technology Services 94560 9,600,000,000
183 Camden New Jersey Campbell's Food Consumer Products 08103 9,600,000,000
184 Byron Center Michigan SpartanNash Wholesalers: Food and Grocery 49315 9,500,000,000
185 Oak Brook Illinois Ace Hardware Wholesalers: Diversified 60523 9,500,000,000
186 Wilmington Massachusetts Analog Devices Semiconductors and Other Electronic Components 01887 9,400,000,000
187 Kingsport Tennessee Eastman Chemical Chemicals 37660 9,400,000,000
188 Parsippany New Jersey Zoetis Pharmaceuticals 07054 9,300,000,000
189 Denver Colorado Ovintiv Mining, Crude-Oil Production 80202 9,200,000,000
190 Merriam Kansas Seaboard Food Production 66202 9,100,000,000
191 Estero Florida Hertz Automotive Retailing, Services 33928 9,000,000,000
192 Manhattan Beach California Skechers U.S.A. Apparel 90266 9,000,000,000
193 Long Island City New York Altice USA Telecommunications 11101 9,000,000,000
194 Mentor Ohio Avery Dennison Packaging, Containers 44060 8,800,000,000
195 Washington District of Columbia Xylem Industrial Machinery 20003 8,600,000,000
196 San Mateo California Franklin Resources Securities 94403 8,500,000,000
197 Allentown Pennsylvania PPL Utilities: Gas and Electric 18101 8,500,000,000
198 Lake Forest Illinois Packaging Corp. of America Packaging, Containers 60045 8,400,000,000
199 Sunnyvale California Intuitive Surgical Medical Products and Equipment 94086 8,400,000,000
200 Downers Grove Illinois Dover Industrial Machinery 60515 8,400,000,000
201 Pleasanton California Workday Computer Software 94588 8,400,000,000
202 Milwaukee Wisconsin Rockwell Automation Electronics, Electrical Equip. 53204 8,300,000,000
203 Maplewood Minnesota Solventum Medical Products and Equipment 55144 8,300,000,000
204 Cincinnati Ohio American Financial Insurance: Property and Casualty (Stock) 45202 8,300,000,000
205 Scottsdale Arizona Taylor Morrison Home Homebuilders 85251 8,200,000,000
206 Chicago Illinois Old Republic International Insurance: Property and Casualty (Stock) 60601 8,200,000,000
207 Orrville Ohio J.M. Smucker Food Consumer Products 44667 8,200,000,000
208 St. Paul Minnesota Securian Financial Insurance: Life, Health (Stock) 55101 8,200,000,000
209 Greenwich Connecticut XPO Transportation and Logistics 06831 8,100,000,000
210 Westerville Ohio Vertiv s Electronics, Electrical Equip. 43082 8,000,000,000
211 Santa Clara California Palo Alto Networks Network and Other Communications Equipment 95054 8,000,000,000
212 New York New York Voya Financial Diversified Financials 10169 8,000,000,000
213 New York New York Foot Locker Specialty Retailers: Apparel 10001 8,000,000,000
214 Toledo Ohio Welltower Real Estate 43615 8,000,000,000
215 Irving Texas Commercial Metals Metals 75039 7,900,000,000
216 Cleveland Ohio TransDigm Aerospace & Defense 44115 7,900,000,000
217 New Braunfels Texas Rush Enterprises Automotive Retailing, Services 78130 7,800,000,000
218 Livonia Michigan Masco Home Equipment, Furnishings 48152 7,800,000,000
219 Warsaw Indiana Zimmer Biomet s Medical Products and Equipment 46580 7,700,000,000
220 San Francisco California Williams-Sonoma Specialty Retailers: Other 94109 7,700,000,000
221 Phoenix Arizona Sprouts Farmers Market Food & Drug Stores 85054 7,700,000,000
222 Houston Texas KBR Information Technology Services 77002 7,700,000,000
223 Chandler Arizona Microchip Technology Semiconductors and Other Electronic Components 85224 7,600,000,000
224 Redwood City California Electronic Arts Entertainment 94065 7,600,000,000
225 Miami Florida Watsco Wholesalers: Diversified 33133 7,600,000,000
226 San Jose California Sanmina Semiconductors and Other Electronic Components 95134 7,600,000,000
227 Atlanta Georgia Newell Brands Home Equipment, Furnishings 30328 7,600,000,000
228 Richmond Virginia ARKO Specialty Retailers: Other 23227 7,600,000,000
229 Jackson Michigan CMS Energy Utilities: Gas and Electric 49201 7,500,000,000
230 Reston Virginia Science Applications International Information Technology Services 20190 7,500,000,000
231 Corona California Monster Beverage Beverages 92879 7,500,000,000
232 Beverly Hills California Endeavor Entertainment 90210 7,500,000,000
233 Winona Minnesota Fastenal Wholesalers: Diversified 55987 7,500,000,000
234 Louisville Kentucky Yum Brands Food Services 40213 7,500,000,000
235 Birmingham Alabama Vulcan Materials Building Materials, Glass 35242 7,400,000,000
236 St. Louis Missouri Core & Main Wholesalers: Diversified 63146 7,400,000,000
237 Westchester Illinois Ingredion Food Production 60154 7,400,000,000
238 Pittsburgh Pennsylvania Howmet Aerospace Aerospace & Defense 15212 7,400,000,000
In [164]:
# Conclusion: fun fact about the Smallest Revenue Company in each City is Walmart is a Double Champion, both as the Biggest Revenue and the Smallest
# due to the fact that Walmart is the only Company in Bentonville goes into Fortune500 list.
In [167]:
# Join the Dataframe 'gdfusact' with 'dfminrevco' for the Top 10
gdfusactminrevco = gdfusact.merge(dfminrevco, how = 'inner', on = ['Zip Code'])
gdfusactminrevco = gdfusactminrevco.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [168]:
mctminrevco = gdfusactminrevco.explore(column='Revenue (rounded)', name='Smallest Revenue Company in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctminrevco)
mctminrevco
Out[168]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [169]:
# Check the Total Revenue in each City
dfcttr = df.groupby(['City','State'], as_index=False)[df.columns[[7]]].sum('Revenue (rounded)').sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
dfcttr
Out[169]:
City State Revenue (rounded)
0 New York New York 1,820,500,000,000
1 Houston Texas 906,500,000,000
2 Seattle Washington 744,900,000,000
3 Bentonville Arkansas 681,000,000,000
4 Atlanta Georgia 489,700,000,000
5 Irving Texas 462,000,000,000
6 Omaha Nebraska 427,000,000,000
7 Eden Prairie Minnesota 418,000,000,000
8 Cupertino California 391,000,000,000
9 Spring Texas 379,700,000,000
10 Woonsocket Rhode Island 372,800,000,000
11 Chicago Illinois 368,100,000,000
12 Dallas Texas 366,500,000,000
13 Mountain View California 366,300,000,000
14 Charlotte North Carolina 331,300,000,000
15 San Francisco California 296,000,000,000
16 Conshohocken Pennsylvania 294,000,000,000
17 Cincinnati Ohio 276,100,000,000
18 Santa Clara California 255,600,000,000
19 Issaquah Washington 254,500,000,000
20 Bloomfield Connecticut 247,100,000,000
21 Redmond Washington 245,100,000,000
22 Indianapolis Indiana 238,900,000,000
23 Dublin Ohio 226,800,000,000
24 Detroit Michigan 216,300,000,000
25 Minneapolis Minnesota 211,400,000,000
26 St. Louis Missouri 207,500,000,000
27 McLean Virginia 197,900,000,000
28 Washington District of Columbia 185,200,000,000
29 Dearborn Michigan 185,000,000,000
30 San Antonio Texas 172,600,000,000
31 Menlo Park California 164,500,000,000
32 Deerfield Illinois 162,800,000,000
33 Arlington Virginia 159,500,000,000
34 San Jose California 153,000,000,000
35 Austin Texas 150,700,000,000
36 Philadelphia Pennsylvania 141,100,000,000
37 Findlay Ohio 140,400,000,000
38 Louisville Kentucky 136,600,000,000
39 Stamford Connecticut 132,500,000,000
40 Richmond Virginia 127,000,000,000
41 Memphis Tennessee 124,800,000,000
42 Bloomington Illinois 123,000,000,000
43 Purchase New York 120,100,000,000
44 Pittsburgh Pennsylvania 119,200,000,000
45 Boston Massachusetts 106,400,000,000
46 Palo Alto California 106,000,000,000
47 Boise Idaho 104,300,000,000
48 Milwaukee Wisconsin 96,700,000,000
49 Bethesda Maryland 96,100,000,000
50 Round Rock Texas 95,600,000,000
51 Burbank California 91,400,000,000
52 Reston Virginia 90,300,000,000
53 Columbus Ohio 90,300,000,000
54 New Brunswick New Jersey 88,800,000,000
55 Miami Florida 85,200,000,000
56 Mooresville North Carolina 83,700,000,000
57 Newark New Jersey 80,700,000,000
58 Cleveland Ohio 79,300,000,000
59 Mayfield Village Ohio 75,400,000,000
60 Fremont California 73,400,000,000
61 Phoenix Arizona 73,000,000,000
62 Jacksonville Florida 71,700,000,000
63 Nashville Tennessee 70,600,000,000
64 San Diego California 64,600,000,000
65 Rahway New Jersey 64,200,000,000
66 Northbrook Illinois 64,100,000,000
67 Armonk New York 62,800,000,000
68 Lakeland Florida 60,200,000,000
69 Waltham Massachusetts 60,100,000,000
70 Providence Rhode Island 57,100,000,000
71 Framingham Massachusetts 56,400,000,000
72 North Chicago Illinois 56,300,000,000
73 Springfield Massachusetts 55,000,000,000
74 Parsippany New Jersey 54,200,000,000
75 Fort Worth Texas 54,200,000,000
76 Springdale Arkansas 53,300,000,000
77 Moline Illinois 51,700,000,000
78 Beaverton Oregon 51,400,000,000
79 Denver Colorado 51,200,000,000
80 St. Paul Minnesota 48,500,000,000
81 Oakland California 48,500,000,000
82 Princeton New Jersey 48,300,000,000
83 Irvine California 48,000,000,000
84 Cambridge Massachusetts 44,600,000,000
85 Bellevue Washington 44,300,000,000
86 St. Petersburg Florida 43,800,000,000
87 Midland Michigan 43,000,000,000
88 Greenwich Connecticut 42,800,000,000
89 Abbott Park Illinois 42,000,000,000
90 Richfield Minnesota 41,500,000,000
91 Newport News Virginia 41,100,000,000
92 Falls Church Virginia 41,000,000,000
93 Long Beach California 40,600,000,000
94 Goodlettsville Tennessee 40,600,000,000
95 Inver Grove Heights Minnesota 39,300,000,000
96 Los Gatos California 39,000,000,000
97 Evendale Ohio 38,700,000,000
98 Norwalk Connecticut 38,300,000,000
99 Rosemont Illinois 37,900,000,000
100 Marlborough Massachusetts 37,200,000,000
101 Arlington Texas 36,800,000,000
102 Medford Oregon 36,600,000,000
103 Columbus Indiana 34,100,000,000
104 Thousand Oaks California 33,400,000,000
105 Tulsa Oklahoma 32,200,000,000
106 Akron Ohio 31,900,000,000
107 Chesapeake Virginia 30,800,000,000
108 Beverly Hills California 30,700,000,000
109 Bloomfield Hills Michigan 30,500,000,000
110 Duluth Georgia 28,900,000,000
111 Foster City California 28,800,000,000
112 Las Vegas Nevada 28,500,000,000
113 Centennial Colorado 27,900,000,000
114 Brentwood Tennessee 27,400,000,000
115 Glen Allen Virginia 27,300,000,000
116 Newport Beach California 27,100,000,000
117 Fort Lauderdale Florida 26,800,000,000
118 Hartford Connecticut 26,500,000,000
119 Westlake Texas 26,000,000,000
120 Raleigh North Carolina 25,900,000,000
121 Englewood Colorado 25,800,000,000
122 Lake Forest Illinois 25,600,000,000
123 Coral Gables Florida 24,900,000,000
124 Juno Beach Florida 24,800,000,000
125 Palm Beach Gardens Florida 24,800,000,000
126 Auburn Hills Michigan 24,500,000,000
127 Riverwoods Illinois 23,600,000,000
128 Baltimore Maryland 23,600,000,000
129 Southfield Michigan 23,300,000,000
130 Tampa Florida 22,900,000,000
131 Portage Michigan 22,600,000,000
132 Chesterfield Missouri 22,100,000,000
133 Scottsdale Arizona 22,000,000,000
134 Maumee Ohio 21,600,000,000
135 Melbourne Florida 21,300,000,000
136 Madison Wisconsin 21,300,000,000
137 Dublin California 21,100,000,000
138 Vernon Hills Illinois 21,000,000,000
139 Allentown Pennsylvania 20,600,000,000
140 Franklin Lakes New Jersey 20,200,000,000
141 Teaneck New Jersey 19,700,000,000
142 Roseland New Jersey 19,200,000,000
143 Toledo Ohio 19,000,000,000
144 Columbus Georgia 18,900,000,000
145 Radnor Pennsylvania 18,400,000,000
146 Long Island City New York 18,300,000,000
147 El Dorado Arkansas 17,900,000,000
148 Rosemead California 17,600,000,000
149 Fort Wayne Indiana 17,500,000,000
150 Birmingham Alabama 16,800,000,000
151 Springfield Missouri 16,700,000,000
152 Benton Harbor Michigan 16,600,000,000
153 Redwood City California 16,300,000,000
154 Chandler Arizona 16,300,000,000
155 Des Peres Missouri 16,300,000,000
156 Menomonee Falls Wisconsin 16,200,000,000
157 Arden Hills Minnesota 16,200,000,000
158 Des Moines Iowa 16,100,000,000
159 Oklahoma City Oklahoma 15,900,000,000
160 Glenview Illinois 15,900,000,000
161 King of Prussia Pennsylvania 15,800,000,000
162 Lansing Michigan 15,800,000,000
163 Woodland Hills California 15,500,000,000
164 Summit New Jersey 15,500,000,000
165 Burlington Massachusetts 15,400,000,000
166 Durham North Carolina 15,400,000,000
167 New Britain Connecticut 15,400,000,000
168 Wallingford Connecticut 15,200,000,000
169 Ankeny Iowa 14,900,000,000
170 Canonsburg Pennsylvania 14,700,000,000
171 Antioch Tennessee 14,400,000,000
172 Farmington Connecticut 14,300,000,000
173 Tarrytown New York 14,200,000,000
174 Tempe Arizona 13,700,000,000
175 Ashburn Virginia 13,700,000,000
176 Buffalo New York 13,500,000,000
177 Coraopolis Pennsylvania 13,400,000,000
178 Erie Pennsylvania 13,200,000,000
179 Monroe Louisiana 13,100,000,000
180 Corning New York 13,100,000,000
181 Burlington North Carolina 13,000,000,000
182 Chattanooga Tennessee 12,900,000,000
183 Melville New York 12,700,000,000
184 Franklin Tennessee 12,600,000,000
185 Wilmington Delaware 12,400,000,000
186 Evansville Indiana 12,300,000,000
187 Westminster Colorado 12,100,000,000
188 Lowell Arkansas 12,100,000,000
189 Plantation Florida 11,900,000,000
190 Austin Minnesota 11,900,000,000
191 New Orleans Louisiana 11,900,000,000
192 Rolling Meadows Illinois 11,600,000,000
193 Orlando Florida 11,400,000,000
194 Reno Nevada 11,300,000,000
195 Plano Texas 11,300,000,000
196 Fairfield Ohio 11,300,000,000
197 Bolingbrook Illinois 11,300,000,000
198 Hershey Pennsylvania 11,200,000,000
199 Midland Texas 11,100,000,000
200 Calhoun Georgia 10,800,000,000
201 Fort Washington Pennsylvania 10,800,000,000
202 Oshkosh Wisconsin 10,700,000,000
203 Burlington New Jersey 10,600,000,000
204 Sumner Washington 10,600,000,000
205 Johnston Rhode Island 10,400,000,000
206 Victor New York 10,000,000,000
207 Elkhart Indiana 10,000,000,000
208 Sunny Isles Beach Florida 10,000,000,000
209 Secaucus New Jersey 9,900,000,000
210 Milpitas California 9,800,000,000
211 Herndon Virginia 9,800,000,000
212 El Segundo California 9,700,000,000
213 Newark California 9,600,000,000
214 Camden New Jersey 9,600,000,000
215 Byron Center Michigan 9,500,000,000
216 Oak Brook Illinois 9,500,000,000
217 Kingsport Tennessee 9,400,000,000
218 Wilmington Massachusetts 9,400,000,000
219 Merriam Kansas 9,100,000,000
220 Estero Florida 9,000,000,000
221 Manhattan Beach California 9,000,000,000
222 Mentor Ohio 8,800,000,000
223 San Mateo California 8,500,000,000
224 Pleasanton California 8,400,000,000
225 Sunnyvale California 8,400,000,000
226 Downers Grove Illinois 8,400,000,000
227 Maplewood Minnesota 8,300,000,000
228 Orrville Ohio 8,200,000,000
229 Westerville Ohio 8,000,000,000
230 Livonia Michigan 7,800,000,000
231 New Braunfels Texas 7,800,000,000
232 Warsaw Indiana 7,700,000,000
233 Jackson Michigan 7,500,000,000
234 Winona Minnesota 7,500,000,000
235 Corona California 7,500,000,000
236 Westchester Illinois 7,400,000,000
In [170]:
# Join the Dataframe 'gdfusact' with 'dfcttr' for the Top 10
dfcttr = dfcttr.merge(df[['City','State','Company','Zip Code']], how = 'inner', on = ['City','State'])
gdfusactcttr = gdfusact.merge(dfcttr, how = 'inner', on = ['Zip Code'])
gdfusactcttr = gdfusactcttr.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [171]:
mcttr = gdfusactcttr.explore(column='Revenue (rounded)', name='Total Revenue in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mcttr)
mcttr
Out[171]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [172]:
# Average revenue in each City
dfctavr = df.groupby(['City','State'], as_index=False)[df.columns[[7]]].mean('Revenue (rounded)').sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
dfctavr
Out[172]:
City State Revenue (rounded)
0 Bentonville Arkansas 681,000,000,000
1 Cupertino California 391,000,000,000
2 Woonsocket Rhode Island 372,800,000,000
3 Conshohocken Pennsylvania 294,000,000,000
4 Issaquah Washington 254,500,000,000
5 Bloomfield Connecticut 247,100,000,000
6 Redmond Washington 245,100,000,000
7 Dublin Ohio 226,800,000,000
8 Eden Prairie Minnesota 209,000,000,000
9 Spring Texas 189,850,000,000
10 Dearborn Michigan 185,000,000,000
11 Mountain View California 183,150,000,000
12 Menlo Park California 164,500,000,000
13 Findlay Ohio 140,400,000,000
14 Seattle Washington 124,150,000,000
15 Bloomington Illinois 123,000,000,000
16 Omaha Nebraska 106,750,000,000
17 Round Rock Texas 95,600,000,000
18 Burbank California 91,400,000,000
19 New Brunswick New Jersey 88,800,000,000
20 San Antonio Texas 86,300,000,000
21 Mooresville North Carolina 83,700,000,000
22 Deerfield Illinois 81,400,000,000
23 Indianapolis Indiana 79,633,333,333
24 Mayfield Village Ohio 75,400,000,000
25 Austin Texas 75,350,000,000
26 Detroit Michigan 72,100,000,000
27 Nashville Tennessee 70,600,000,000
28 Philadelphia Pennsylvania 70,550,000,000
29 Rahway New Jersey 64,200,000,000
30 Northbrook Illinois 64,100,000,000
31 Armonk New York 62,800,000,000
32 Washington District of Columbia 61,733,333,333
33 Lakeland Florida 60,200,000,000
34 Purchase New York 60,050,000,000
35 Irving Texas 57,750,000,000
36 Framingham Massachusetts 56,400,000,000
37 North Chicago Illinois 56,300,000,000
38 Charlotte North Carolina 55,216,666,667
39 Fort Worth Texas 54,200,000,000
40 Springdale Arkansas 53,300,000,000
41 Arlington Virginia 53,166,666,667
42 Palo Alto California 53,000,000,000
43 Boise Idaho 52,150,000,000
44 Moline Illinois 51,700,000,000
45 Beaverton Oregon 51,400,000,000
46 McLean Virginia 49,475,000,000
47 Princeton New Jersey 48,300,000,000
48 Bethesda Maryland 48,050,000,000
49 Irvine California 48,000,000,000
50 Cincinnati Ohio 46,016,666,667
51 Louisville Kentucky 45,533,333,333
52 Midland Michigan 43,000,000,000
53 Santa Clara California 42,600,000,000
54 New York New York 42,337,209,302
55 Abbott Park Illinois 42,000,000,000
56 Memphis Tennessee 41,600,000,000
57 St. Louis Missouri 41,500,000,000
58 Richfield Minnesota 41,500,000,000
59 Falls Church Virginia 41,000,000,000
60 Dallas Texas 40,722,222,222
61 Long Beach California 40,600,000,000
62 Goodlettsville Tennessee 40,600,000,000
63 Newark New Jersey 40,350,000,000
64 Inver Grove Heights Minnesota 39,300,000,000
65 Los Gatos California 39,000,000,000
66 Evendale Ohio 38,700,000,000
67 Rosemont Illinois 37,900,000,000
68 Houston Texas 37,770,833,333
69 Atlanta Georgia 37,669,230,769
70 Arlington Texas 36,800,000,000
71 Fremont California 36,700,000,000
72 Medford Oregon 36,600,000,000
73 Minneapolis Minnesota 35,233,333,333
74 Columbus Indiana 34,100,000,000
75 Thousand Oaks California 33,400,000,000
76 Stamford Connecticut 33,125,000,000
77 San Francisco California 32,888,888,889
78 Chesapeake Virginia 30,800,000,000
79 Bloomfield Hills Michigan 30,500,000,000
80 Columbus Ohio 30,100,000,000
81 Waltham Massachusetts 30,050,000,000
82 Foster City California 28,800,000,000
83 Miami Florida 28,400,000,000
84 Centennial Colorado 27,900,000,000
85 Springfield Massachusetts 27,500,000,000
86 Fort Lauderdale Florida 26,800,000,000
87 Hartford Connecticut 26,500,000,000
88 Chicago Illinois 26,292,857,143
89 Westlake Texas 26,000,000,000
90 Richmond Virginia 25,400,000,000
91 Palm Beach Gardens Florida 24,800,000,000
92 Juno Beach Florida 24,800,000,000
93 Oakland California 24,250,000,000
94 Baltimore Maryland 23,600,000,000
95 Riverwoods Illinois 23,600,000,000
96 Southfield Michigan 23,300,000,000
97 Portage Michigan 22,600,000,000
98 Cambridge Massachusetts 22,300,000,000
99 Bellevue Washington 22,150,000,000
100 Chesterfield Missouri 22,100,000,000
101 St. Petersburg Florida 21,900,000,000
102 San Jose California 21,857,142,857
103 San Diego California 21,533,333,333
104 Madison Wisconsin 21,300,000,000
105 Melbourne Florida 21,300,000,000
106 Boston Massachusetts 21,280,000,000
107 Dublin California 21,100,000,000
108 Vernon Hills Illinois 21,000,000,000
109 Newport News Virginia 20,550,000,000
110 Franklin Lakes New Jersey 20,200,000,000
111 Teaneck New Jersey 19,700,000,000
112 Milwaukee Wisconsin 19,340,000,000
113 Roseland New Jersey 19,200,000,000
114 Norwalk Connecticut 19,150,000,000
115 Providence Rhode Island 19,033,333,333
116 Columbus Georgia 18,900,000,000
117 Marlborough Massachusetts 18,600,000,000
118 Radnor Pennsylvania 18,400,000,000
119 Phoenix Arizona 18,250,000,000
120 Parsippany New Jersey 18,066,666,667
121 Reston Virginia 18,060,000,000
122 Jacksonville Florida 17,925,000,000
123 El Dorado Arkansas 17,900,000,000
124 Rosemead California 17,600,000,000
125 Fort Wayne Indiana 17,500,000,000
126 Pittsburgh Pennsylvania 17,028,571,429
127 Springfield Missouri 16,700,000,000
128 Benton Harbor Michigan 16,600,000,000
129 Des Peres Missouri 16,300,000,000
130 Menomonee Falls Wisconsin 16,200,000,000
131 Arden Hills Minnesota 16,200,000,000
132 St. Paul Minnesota 16,166,666,667
133 Tulsa Oklahoma 16,100,000,000
134 Des Moines Iowa 16,100,000,000
135 Akron Ohio 15,950,000,000
136 Glenview Illinois 15,900,000,000
137 Oklahoma City Oklahoma 15,900,000,000
138 Cleveland Ohio 15,860,000,000
139 Lansing Michigan 15,800,000,000
140 King of Prussia Pennsylvania 15,800,000,000
141 Woodland Hills California 15,500,000,000
142 Summit New Jersey 15,500,000,000
143 Durham North Carolina 15,400,000,000
144 Burlington Massachusetts 15,400,000,000
145 New Britain Connecticut 15,400,000,000
146 Beverly Hills California 15,350,000,000
147 Wallingford Connecticut 15,200,000,000
148 Ankeny Iowa 14,900,000,000
149 Canonsburg Pennsylvania 14,700,000,000
150 Duluth Georgia 14,450,000,000
151 Antioch Tennessee 14,400,000,000
152 Farmington Connecticut 14,300,000,000
153 Las Vegas Nevada 14,250,000,000
154 Tarrytown New York 14,200,000,000
155 Ashburn Virginia 13,700,000,000
156 Tempe Arizona 13,700,000,000
157 Brentwood Tennessee 13,700,000,000
158 Glen Allen Virginia 13,650,000,000
159 Newport Beach California 13,550,000,000
160 Buffalo New York 13,500,000,000
161 Coraopolis Pennsylvania 13,400,000,000
162 Erie Pennsylvania 13,200,000,000
163 Corning New York 13,100,000,000
164 Monroe Louisiana 13,100,000,000
165 Burlington North Carolina 13,000,000,000
166 Raleigh North Carolina 12,950,000,000
167 Chattanooga Tennessee 12,900,000,000
168 Englewood Colorado 12,900,000,000
169 Denver Colorado 12,800,000,000
170 Lake Forest Illinois 12,800,000,000
171 Melville New York 12,700,000,000
172 Franklin Tennessee 12,600,000,000
173 Coral Gables Florida 12,450,000,000
174 Wilmington Delaware 12,400,000,000
175 Evansville Indiana 12,300,000,000
176 Auburn Hills Michigan 12,250,000,000
177 Westminster Colorado 12,100,000,000
178 Lowell Arkansas 12,100,000,000
179 Austin Minnesota 11,900,000,000
180 Plantation Florida 11,900,000,000
181 New Orleans Louisiana 11,900,000,000
182 Rolling Meadows Illinois 11,600,000,000
183 Tampa Florida 11,450,000,000
184 Orlando Florida 11,400,000,000
185 Reno Nevada 11,300,000,000
186 Plano Texas 11,300,000,000
187 Fairfield Ohio 11,300,000,000
188 Bolingbrook Illinois 11,300,000,000
189 Hershey Pennsylvania 11,200,000,000
190 Midland Texas 11,100,000,000
191 Scottsdale Arizona 11,000,000,000
192 Calhoun Georgia 10,800,000,000
193 Fort Washington Pennsylvania 10,800,000,000
194 Maumee Ohio 10,800,000,000
195 Greenwich Connecticut 10,700,000,000
196 Oshkosh Wisconsin 10,700,000,000
197 Burlington New Jersey 10,600,000,000
198 Sumner Washington 10,600,000,000
199 Johnston Rhode Island 10,400,000,000
200 Allentown Pennsylvania 10,300,000,000
201 Victor New York 10,000,000,000
202 Sunny Isles Beach Florida 10,000,000,000
203 Elkhart Indiana 10,000,000,000
204 Secaucus New Jersey 9,900,000,000
205 Milpitas California 9,800,000,000
206 Herndon Virginia 9,800,000,000
207 El Segundo California 9,700,000,000
208 Newark California 9,600,000,000
209 Camden New Jersey 9,600,000,000
210 Toledo Ohio 9,500,000,000
211 Oak Brook Illinois 9,500,000,000
212 Byron Center Michigan 9,500,000,000
213 Wilmington Massachusetts 9,400,000,000
214 Kingsport Tennessee 9,400,000,000
215 Long Island City New York 9,150,000,000
216 Merriam Kansas 9,100,000,000
217 Estero Florida 9,000,000,000
218 Manhattan Beach California 9,000,000,000
219 Mentor Ohio 8,800,000,000
220 San Mateo California 8,500,000,000
221 Pleasanton California 8,400,000,000
222 Downers Grove Illinois 8,400,000,000
223 Birmingham Alabama 8,400,000,000
224 Sunnyvale California 8,400,000,000
225 Maplewood Minnesota 8,300,000,000
226 Orrville Ohio 8,200,000,000
227 Redwood City California 8,150,000,000
228 Chandler Arizona 8,150,000,000
229 Westerville Ohio 8,000,000,000
230 Livonia Michigan 7,800,000,000
231 New Braunfels Texas 7,800,000,000
232 Warsaw Indiana 7,700,000,000
233 Jackson Michigan 7,500,000,000
234 Corona California 7,500,000,000
235 Winona Minnesota 7,500,000,000
236 Westchester Illinois 7,400,000,000
In [173]:
# Fun fact: again, Bentonville is the Champion due to the only one Company made it into Fortune500 list.
In [174]:
# Join the Dataframe 'gdfusact' with 'dfctavr' for the Top 10
dfctavr = dfctavr.merge(df[['City','State','Company','Zip Code']], how = 'inner', on = ['City','State'])
gdfusactctavr = gdfusact.merge(dfctavr, how = 'inner', on = ['Zip Code'])
gdfusactctavr = gdfusactctavr.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [175]:
mctctavr = gdfusactctavr.explore(column='Revenue (rounded)', name='Average Revenue in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctctavr)
mctctavr
Out[175]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [176]:
# Check the Largest Employer Company in each City
dfmaxempco = df.head(1)

for ct in ctslist[0:]:
    dfct = df.where(df['City'] == ct[0]).where(df['State'] == ct[1]).dropna()
    mnmaxemp = dfct['Employees'].max()
    dfctmaxempco = dfct.where(dfct['Employees'] == mnmaxemp).dropna()
    dfmaxempco = pd.concat([dfmaxempco, dfctmaxempco], ignore_index=True)
    
dfmaxempco = dfmaxempco.drop(0)
dfmaxempco[['City','State','Company','Industry','Zip Code','Employees']].sort_values(by='Employees', ascending=False).reset_index(drop=True)
Out[176]:
City State Company Industry Zip Code Employees
0 Bentonville Arkansas Walmart General Merchandisers 72712 2,100,000
1 Seattle Washington Amazon Internet Services and Retailing 98109 1,556,000
2 Atlanta Georgia Home Depot Specialty Retailers: Other 30339 470,100
3 Newark California Concentrix Information Technology Services 94560 450,000
4 Minneapolis Minnesota Target General Merchandisers 55403 440,000
5 Memphis Tennessee FedEx Mail, Package and Freight Delivery 38120 422,100
6 Cincinnati Ohio Kroger Food & Drug Stores 45202 409,000
7 Eden Prairie Minnesota UnitedHealth Health Care: Insurance and Managed Care 55344 400,000
8 Omaha Nebraska Berkshire Hathaway Insurance: Property and Casualty (Stock) 68131 392,400
9 Framingham Massachusetts TJX Specialty Retailers: Apparel 01701 364,000
10 Teaneck New Jersey Cognizant Technology Information Technology Services 07666 336,800
11 Issaquah Washington Costco General Merchandisers 98027 333,000
12 Purchase New York PepsiCo Food Consumer Products 10577 319,000
13 New York New York JPMorgan Chase Commercial Banks 10017 317,200
14 Armonk New York IBM Information Technology Services 10504 284,500
15 Nashville Tennessee HCA Healthcare Health Care: Medical Facilities 37203 271,000
16 Philadelphia Pennsylvania Aramark Diversified Outsourcing Services 19103 266,700
17 Woonsocket Rhode Island CVS Health Health Care: Pharmacy and Other Services 02895 259,500
18 Lakeland Florida Publix Super Markets Food & Drug Stores 33811 255,000
19 Deerfield Illinois Walgreens Food & Drug Stores 60015 252,500
20 Plano Texas Yum China s Food Services 75074 245,500
21 Redmond Washington Microsoft Computer Software 98052 228,000
22 San Francisco California Wells Fargo Commercial Banks 94104 217,500
23 Mooresville North Carolina Lowe's Specialty Retailers: Other 28117 215,500
24 Charlotte North Carolina Bank of America Commercial Banks 28255 213,200
25 Burbank California Walt Disney Entertainment 91521 205,000
26 Boise Idaho Albertsons Food & Drug Stores 83706 196,600
27 Goodlettsville Tennessee Dollar General Specialty Retailers: Other 37072 194,200
28 Orlando Florida Darden Restaurants Food Services 32837 191,100
29 Arlington Virginia RTX Aerospace & Defense 22209 186,000
30 Mountain View California Alphabet Internet Services and Retailing 94043 183,300
31 McLean Virginia Hilton Hotels, Casinos, Resorts 22102 181,000
32 Southfield Michigan Lear Motor Vehicles & Parts 48033 173,700
33 Dearborn Michigan Ford Motor Motor Vehicles & Parts 48126 171,000
34 Cupertino California Apple Computers, Office Equipment 95014 164,000
35 Detroit Michigan General Motors Motor Vehicles & Parts 48265 162,000
36 Austin Texas Oracle Computer Software 78741 159,000
37 Bethesda Maryland Marriott International Hotels, Casinos, Resorts 20814 155,000
38 Chicago Illinois McDonald's Food Services 60607 150,000
39 Dallas Texas AT&T Telecommunications 75202 141,000
40 Chesapeake Virginia Dollar Tree Specialty Retailers: Other 23320 139,600
41 New Brunswick New Jersey Johnson & Johnson Pharmaceuticals 08933 138,100
42 Springdale Arkansas Tyson Foods Food Production 72762 138,000
43 St. Petersburg Florida Jabil Semiconductors and Other Electronic Components 33716 138,000
44 Fort Worth Texas American Airlines Airlines 76155 133,300
45 Newport Beach California Chipotle Mexican Grill Food Services 92660 130,500
46 Ashburn Virginia DXC Technology Information Technology Services 20147 130,000
47 Greenwich Connecticut GXO Logistics Transportation and Logistics 06831 128,500
48 Wallingford Connecticut Amphenol Network and Other Communications Equipment 06492 125,000
49 Waltham Massachusetts Thermo Fisher Scientific Scientific, Photographic and Control Equipment 02451 125,000
50 Reston Virginia General Dynamics Aerospace & Defense 20190 117,000
51 Abbott Park Illinois Abbott Laboratories Medical Products and Equipment 60064 114,000
52 Irving Texas Caterpillar Construction and Farm Machinery 75039 112,900
53 Santa Clara California Intel Semiconductors and Other Electronic Components 95054 108,900
54 Round Rock Texas Dell Technologies Computers, Office Equipment 78682 108,000
55 Dublin California Ross Stores Specialty Retailers: Apparel 94568 107,000
56 Indianapolis Indiana Elevance Health Health Care: Insurance and Managed Care 46204 103,700
57 Falls Church Virginia Northrop Grumman Aerospace & Defense 22042 97,000
58 Stamford Connecticut Charter Communications Telecommunications 06902 94,500
59 San Jose California Cisco Systems Network and Other Communications Equipment 95134 90,400
60 Durham North Carolina IQVIA s Health Care: Pharmacy and Other Services 27703 88,000
61 King of Prussia Pennsylvania Universal Health Services Health Care: Medical Facilities 19406 87,500
62 Springfield Missouri O'Reilly Automotive Specialty Retailers: Other 65802 85,600
63 Richfield Minnesota Best Buy Specialty Retailers: Other 55423 85,000
64 Beaverton Oregon Nike Apparel 97005 79,400
65 Cambridge Massachusetts GE Vernova Energy 02141 76,800
66 Houston Texas Sysco Wholesalers: Food and Grocery 77077 76,000
67 Denver Colorado DaVita Health Care: Medical Facilities 80202 76,000
68 Menlo Park California Meta Internet Services and Retailing 94025 74,100
69 Franklin Lakes New Jersey Becton Dickinson Medical Products and Equipment 07417 74,000
70 Rahway New Jersey Merck Pharmaceuticals 07065 74,000
71 St. Louis Missouri Emerson Electric Industrial Machinery 63136 73,000
72 Bloomfield Connecticut Cigna Health Care: Pharmacy and Other Services 06002 72,400
73 Farmington Connecticut Otis Worldwide Industrial Machinery 06032 72,000
74 Columbus Indiana Cummins Industrial Machinery 47201 69,600
75 Las Vegas Nevada MGM Resorts International Hotels, Casinos, Resorts 89109 69,000
76 Akron Ohio Goodyear Tire & Rubber Motor Vehicles & Parts 44316 68,000
77 Bloomington Illinois State Farm Insurance: Property and Casualty (Mutual) 61710 67,400
78 Mayfield Village Ohio Progressive Insurance: Property and Casualty (Stock) 44143 66,300
79 Louisville Kentucky Humana Health Care: Insurance and Managed Care 40202 65,700
80 Burlington North Carolina Labcorp s Health Care: Pharmacy and Other Services 27215 65,400
81 Roseland New Jersey Automatic Data Processing Diversified Outsourcing Services 07068 64,000
82 Cleveland Ohio Sherwin-Williams Chemicals 44115 63,900
83 Auburn Hills Michigan Autoliv Motor Vehicles & Parts 48326 62,300
84 Washington District of Columbia Danaher Medical Products and Equipment 20037 62,000
85 St. Paul Minnesota 3M Chemicals 55144 61,500
86 Spring Texas Hewlett Packard Computers, Office Equipment 77389 61,000
87 Menomonee Falls Wisconsin Kohl's General Merchandisers 53051 60,000
88 Palo Alto California HP Computers, Office Equipment 94304 58,000
89 Corning New York Corning Electronics, Electrical Equip. 14831 56,300
90 Rolling Meadows Illinois Arthur J. Gallagher Diversified Financials 60008 56,000
91 Moline Illinois Deere Construction and Farm Machinery 61265 55,500
92 Northbrook Illinois Allstate Insurance: Property and Casualty (Stock) 60062 55,200
93 North Chicago Illinois AbbVie Pharmaceuticals 60064 55,000
94 Des Peres Missouri Edward Jones Securities 63131 55,000
95 Pittsburgh Pennsylvania PNC Commercial Banks 15222 54,400
96 Marlborough Massachusetts Boston Scientific Medical Products and Equipment 01752 53,000
97 Evendale Ohio General Electric Aerospace & Defense 45215 53,000
98 Portage Michigan Stryker Medical Products and Equipment 49002 53,000
99 Boston Massachusetts State Street Commercial Banks 02114 52,600
100 Franklin Tennessee Community Health Systems Health Care: Medical Facilities 37067 52,500
101 Coral Gables Florida Ryder System Transportation and Logistics 33134 50,700
102 Secaucus New Jersey Quest Diagnostics Health Care: Pharmacy and Other Services 07094 50,500
103 Jacksonville Florida Fidelity National Information Financial Data Services 32202 50,000
104 Reno Nevada Caesars Entertainment Hotels, Casinos, Resorts 89501 50,000
105 San Diego California Qualcomm Semiconductors and Other Electronic Components 92121 49,000
106 New Britain Connecticut Stanley Black & Decker Industrial Machinery 06053 48,500
107 Dublin Ohio Cardinal Health Wholesalers: Health Care 43017 48,400
108 Palm Beach Gardens Florida Carrier Global Industrial Machinery 33418 48,000
109 Raleigh North Carolina Advance Auto Parts Specialty Retailers: Other 27609 48,000
110 Burlington New Jersey Burlington Stores Specialty Retailers: Apparel 08016 47,300
111 Antioch Tennessee LKQ Wholesalers: Diversified 37013 47,000
112 Melbourne Florida L3Harris Technologies Aerospace & Defense 32919 47,000
113 Newport News Virginia Huntington Ingalls Industries Aerospace & Defense 23607 44,000
114 Glenview Illinois Illinois Tool Works Industrial Machinery 60025 44,000
115 Conshohocken Pennsylvania Cencora Wholesalers: Health Care 19428 44,000
116 Benton Harbor Michigan Whirlpool Electronics, Electrical Equip. 49022 44,000
117 Phoenix Arizona Republic Services Waste Management 85054 42,000
118 Evansville Indiana Berry Global Packaging, Containers 47710 42,000
119 Calhoun Georgia Mohawk Industries Home Equipment, Furnishings 30701 41,900
120 Norwalk Connecticut EMCOR Engineering & Construction 06851 40,400
121 Maumee Ohio Dana Motor Vehicles & Parts 43537 39,600
122 Sumner Washington Lululemon athletica Specialty Retailers: Apparel 98390 39,000
123 Brentwood Tennessee Tractor Supply Specialty Retailers: Other 37027 39,000
124 Bolingbrook Illinois Ulta Beauty Specialty Retailers: Other 60440 39,000
125 San Antonio Texas USAA Insurance: Property and Casualty (Stock) 78288 38,000
126 Milwaukee Wisconsin Fiserv Financial Data Services 53203 38,000
127 Newark New Jersey Prudential Financial Insurance: Life, Health (Stock) 07102 37,900
128 Coraopolis Pennsylvania Dick's Sporting Goods Specialty Retailers: Other 15108 37,400
129 Richmond Virginia Performance Food Wholesalers: Food and Grocery 23238 36,800
130 Midland Michigan Dow Chemicals 48674 36,000
131 Mentor Ohio Avery Dennison Packaging, Containers 44060 35,000
132 Princeton New Jersey Bristol-Myers Squibb Pharmaceuticals 08543 34,100
133 Providence Rhode Island Textron Aerospace & Defense 02903 34,000
134 Lowell Arkansas J.B. Hunt Transport Services Trucking, Truck Leasing 72745 33,600
135 Ankeny Iowa Casey's General Stores Specialty Retailers: Other 50021 33,100
136 Westlake Texas Charles Schwab Securities 76262 32,100
137 Canonsburg Pennsylvania Viatris Pharmaceuticals 15317 32,000
138 Westerville Ohio Vertiv s Electronics, Electrical Equip. 43082 31,000
139 Medford Oregon Lithia Motors Automotive Retailing, Services 97501 30,200
140 Bellevue Washington Paccar Motor Vehicles & Parts 98004 30,100
141 Rosemont Illinois US Foods Wholesalers: Food and Grocery 60018 30,000
142 Burlington Massachusetts Keurig Dr Pepper Beverages 01803 29,400
143 Bloomfield Hills Michigan Penske Automotive Automotive Retailing, Services 48302 28,900
144 Oakland California PG&E Utilities: Gas and Electric 94612 28,400
145 Thousand Oaks California Amgen Pharmaceuticals 91320 28,000
146 Irvine California Ingram Micro Wholesalers: Electronics and Office Equipment 92612 26,100
147 Estero Florida Hertz Automotive Retailing, Services 33928 26,000
148 Fremont California TD Synnex Wholesalers: Electronics and Office Equipment 94538 25,800
149 Fort Lauderdale Florida AutoNation Automotive Retailing, Services 33301 25,100
150 Toledo Ohio Owens Corning Building Materials, Glass 43659 25,000
151 Lake Forest Illinois W.W. Grainger Wholesalers: Diversified 60045 25,000
152 Melville New York Henry Schein Wholesalers: Health Care 11747 25,000
153 Monroe Louisiana Lumen Technologies Telecommunications 71203 25,000
154 Beverly Hills California Live Nation Entertainment Entertainment 90210 24,200
155 Downers Grove Illinois Dover Industrial Machinery 60515 24,000
156 Duluth Georgia AGCO Construction and Farm Machinery 30096 24,000
157 Wilmington Massachusetts Analog Devices Semiconductors and Other Electronic Components 01887 24,000
158 Wilmington Delaware DuPont Chemicals 19805 24,000
159 Glen Allen Virginia Owens & Minor Wholesalers: Health Care 23060 23,200
160 Tampa Florida Crown s Packaging, Containers 33637 23,000
161 Columbus Ohio Nationwide Insurance: Property and Casualty (Mutual) 43215 22,500
162 Allentown Pennsylvania Air Products & Chemicals Chemicals 18106 22,400
163 Chandler Arizona Microchip Technology Semiconductors and Other Electronic Components 85224 22,300
164 Elkhart Indiana THOR Industries Motor Vehicles & Parts 46514 22,300
165 Buffalo New York M&T Bank Commercial Banks 14203 22,100
166 Summit New Jersey Kenvue Household and Personal Products 07901 22,000
167 Maplewood Minnesota Solventum Medical Products and Equipment 55144 22,000
168 Centennial Colorado Arrow Electronics Wholesalers: Electronics and Office Equipment 80112 21,500
169 Winona Minnesota Fastenal Wholesalers: Diversified 55987 21,000
170 Riverwoods Illinois Discover Financial Diversified Financials 60015 21,000
171 Pleasanton California Workday Computer Software 94588 20,500
172 Parsippany New Jersey Avis Budget Automotive Retailing, Services 07054 20,500
173 Austin Minnesota Hormel Foods Food Consumer Products 55912 20,000
174 Long Island City New York JetBlue Airways Airlines 11101 19,800
175 Des Moines Iowa Principal Financial Insurance: Life, Health (Stock) 50392 19,700
176 Birmingham Alabama Regions Financial Commercial Banks 35203 19,600
177 Hershey Pennsylvania Hershey Food Consumer Products 17033 19,300
178 Hartford Connecticut Hartford Insurance Insurance: Property and Casualty (Stock) 06155 19,100
179 Englewood Colorado QVC Internet Services and Retailing 80112 19,000
180 Oshkosh Wisconsin Oshkosh Construction and Farm Machinery 54902 18,500
181 Findlay Ohio Marathon Petroleum Petroleum Refining 45840 18,300
182 Plantation Florida Chewy Internet Services and Retailing 33322 18,000
183 Long Beach California Molina Healthcare Health Care: Insurance and Managed Care 90802 18,000
184 Livonia Michigan Masco Home Equipment, Furnishings 48152 18,000
185 Foster City California Gilead Sciences Pharmaceuticals 94404 17,600
186 Tempe Arizona Carvana Automotive Retailing, Services 85281 17,400
187 Warsaw Indiana Zimmer Biomet s Medical Products and Equipment 46580 17,000
188 Juno Beach Florida NextEra Energy Utilities: Gas and Electric 33408 16,800
189 Scottsdale Arizona Reliance Metals 85254 16,000
190 Westminster Colorado Ball Packaging, Containers 80021 16,000
191 Sunnyvale California Intuitive Surgical Medical Products and Equipment 94086 15,600
192 Tarrytown New York Regeneron Pharmaceuticals Pharmaceuticals 10591 15,100
193 Manhattan Beach California Skechers U.S.A. Apparel 90266 15,100
194 Vernon Hills Illinois CDW Information Technology Services 60061 15,100
195 Milpitas California KLA Semiconductors and Other Electronic Components 95035 15,100
196 Sunny Isles Beach Florida Icahn Enterprises Diversified Financials 33160 15,000
197 Byron Center Michigan SpartanNash Wholesalers: Food and Grocery 49315 15,000
198 Arlington Texas D.R. Horton Homebuilders 76011 14,800
199 Camden New Jersey Campbell's Food Consumer Products 08103 14,400
200 Baltimore Maryland Constellation Energy Energy 21231 14,200
201 Kingsport Tennessee Eastman Chemical Chemicals 37660 14,000
202 Merriam Kansas Seaboard Food Production 66202 14,000
203 Rosemead California Edison International Utilities: Gas and Electric 91770 14,000
204 Los Gatos California Netflix Entertainment 95032 14,000
205 Redwood City California Electronic Arts Entertainment 94065 13,700
206 Miami Florida Lennar Homebuilders 33126 13,300
207 Fort Wayne Indiana Steel Dynamics Metals 46804 13,000
208 Columbus Georgia Aflac Insurance: Life, Health (Stock) 31999 12,700
209 Oak Brook Illinois Ace Hardware Wholesalers: Diversified 60523 12,500
210 New Orleans Louisiana Entergy Utilities: Gas and Electric 70113 12,300
211 El Dorado Arkansas Murphy USA Specialty Retailers: Other 71730 11,600
212 Springfield Massachusetts Mass Mutual Insurance: Life, Health (Mutual) 01111 11,200
213 Westchester Illinois Ingredion Food Production 60154 11,200
214 Madison Wisconsin American Family Insurance Insurance: Property and Casualty (Stock) 53783 11,100
215 Chattanooga Tennessee Unum Insurance: Life, Health (Stock) 37402 10,900
216 Inver Grove Heights Minnesota CHS Food Production 55077 10,700
217 San Mateo California Franklin Resources Securities 94403 10,200
218 Woodland Hills California Farmers Insurance Exchange Insurance: Property and Casualty (Mutual) 91367 9,900
219 Radnor Pennsylvania Lincoln National Insurance: Life, Health (Stock) 19087 9,800
220 Victor New York Constellation Brands Beverages 14564 9,300
221 Arden Hills Minnesota Land O'Lakes Food Consumer Products 55126 9,000
222 Orrville Ohio J.M. Smucker Food Consumer Products 44667 9,000
223 Jackson Michigan CMS Energy Utilities: Gas and Electric 49201 8,300
224 Herndon Virginia QXO Building Products Wholesalers: Diversified 20170 8,100
225 New Braunfels Texas Rush Enterprises Automotive Retailing, Services 78130 7,900
226 Lansing Michigan Auto-Owners Insurance Insurance: Property and Casualty (Mutual) 48917 7,300
227 Erie Pennsylvania Erie Insurance Insurance: Property and Casualty (Mutual) 16530 6,700
228 Corona California Monster Beverage Beverages 92879 6,000
229 Tulsa Oklahoma Williams Pipelines 74172 5,800
230 Johnston Rhode Island FM Insurance: Property and Casualty (Stock) 02919 5,800
231 Fairfield Ohio Cincinnati Financial Insurance: Property and Casualty (Stock) 45014 5,600
232 Fort Washington Pennsylvania Toll Brothers Homebuilders 19034 4,900
233 Chesterfield Missouri Reinsurance of America Insurance: Life, Health (Stock) 63017 4,100
234 Oklahoma City Oklahoma Devon Energy Mining, Crude-Oil Production 73102 2,300
235 Midland Texas Diamondback Energy Mining, Crude-Oil Production 79701 2,000
236 El Segundo California A-Mark Precious Metals Wholesalers: Diversified 90245 500
In [177]:
# Join the Dataframe 'gdfusact' with 'dfmaxempco' for the Top 10
gdfusactmaxempco = gdfusact.merge(dfmaxempco, how = 'inner', on = ['Zip Code'])
gdfusactmaxempco = gdfusactmaxempco.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [178]:
mctmaxempco = gdfusactmaxempco.explore(column='Revenue (rounded)', name='Biggest Employer Company in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctmaxempco)
mctmaxempco
Out[178]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [182]:
# Check the Smallest Employer Company in each City
dfminempco = df.head(1)

for ct in ctslist[0:]:
    dfct = df.where(df['City'] == ct[0]).where(df['State'] == ct[1]).dropna()
    mnminemp = dfct['Employees'].min()
    dfctminempco = dfct.where(dfct['Employees'] == mnminemp).dropna()
    dfminempco = pd.concat([dfminempco, dfctminempco], ignore_index=True)
    
dfminempco = dfminempco.drop(0)
dfminempco[['City','State','Company','Industry','Zip Code','Employees']].sort_values(by='Employees', ascending=False).reset_index(drop=True)
Out[182]:
City State Company Industry Zip Code Employees
0 Bentonville Arkansas Walmart General Merchandisers 72712 2,100,000
1 Newark California Concentrix Information Technology Services 94560 450,000
2 Framingham Massachusetts TJX Specialty Retailers: Apparel 01701 364,000
3 Teaneck New Jersey Cognizant Technology Information Technology Services 07666 336,800
4 Issaquah Washington Costco General Merchandisers 98027 333,000
5 Armonk New York IBM Information Technology Services 10504 284,500
6 Nashville Tennessee HCA Healthcare Health Care: Medical Facilities 37203 271,000
7 Woonsocket Rhode Island CVS Health Health Care: Pharmacy and Other Services 02895 259,500
8 Lakeland Florida Publix Super Markets Food & Drug Stores 33811 255,000
9 Plano Texas Yum China s Food Services 75074 245,500
10 Redmond Washington Microsoft Computer Software 98052 228,000
11 Mooresville North Carolina Lowe's Specialty Retailers: Other 28117 215,500
12 Burbank California Walt Disney Entertainment 91521 205,000
13 Goodlettsville Tennessee Dollar General Specialty Retailers: Other 37072 194,200
14 Orlando Florida Darden Restaurants Food Services 32837 191,100
15 Philadelphia Pennsylvania Comcast Telecommunications 19103 182,000
16 Southfield Michigan Lear Motor Vehicles & Parts 48033 173,700
17 Dearborn Michigan Ford Motor Motor Vehicles & Parts 48126 171,000
18 Cupertino California Apple Computers, Office Equipment 95014 164,000
19 Chesapeake Virginia Dollar Tree Specialty Retailers: Other 23320 139,600
20 New Brunswick New Jersey Johnson & Johnson Pharmaceuticals 08933 138,100
21 Springdale Arkansas Tyson Foods Food Production 72762 138,000
22 Fort Worth Texas American Airlines Airlines 76155 133,300
23 Ashburn Virginia DXC Technology Information Technology Services 20147 130,000
24 Austin Texas Tesla Motor Vehicles & Parts 78725 125,700
25 Wallingford Connecticut Amphenol Network and Other Communications Equipment 06492 125,000
26 Bethesda Maryland Lockheed Martin Aerospace & Defense 20817 121,000
27 Abbott Park Illinois Abbott Laboratories Medical Products and Equipment 60064 114,000
28 Round Rock Texas Dell Technologies Computers, Office Equipment 78682 108,000
29 Dublin California Ross Stores Specialty Retailers: Apparel 94568 107,000
30 Falls Church Virginia Northrop Grumman Aerospace & Defense 22042 97,000
31 Durham North Carolina IQVIA s Health Care: Pharmacy and Other Services 27703 88,000
32 King of Prussia Pennsylvania Universal Health Services Health Care: Medical Facilities 19406 87,500
33 Springfield Missouri O'Reilly Automotive Specialty Retailers: Other 65802 85,600
34 Richfield Minnesota Best Buy Specialty Retailers: Other 55423 85,000
35 Beaverton Oregon Nike Apparel 97005 79,400
36 Menlo Park California Meta Internet Services and Retailing 94025 74,100
37 Franklin Lakes New Jersey Becton Dickinson Medical Products and Equipment 07417 74,000
38 Rahway New Jersey Merck Pharmaceuticals 07065 74,000
39 Bloomfield Connecticut Cigna Health Care: Pharmacy and Other Services 06002 72,400
40 Farmington Connecticut Otis Worldwide Industrial Machinery 06032 72,000
41 Columbus Indiana Cummins Industrial Machinery 47201 69,600
42 Bloomington Illinois State Farm Insurance: Property and Casualty (Mutual) 61710 67,400
43 Mayfield Village Ohio Progressive Insurance: Property and Casualty (Stock) 44143 66,300
44 Burlington North Carolina Labcorp s Health Care: Pharmacy and Other Services 27215 65,400
45 Roseland New Jersey Automatic Data Processing Diversified Outsourcing Services 07068 64,000
46 Spring Texas Exxon Mobil Petroleum Refining 77389 60,900
47 Menomonee Falls Wisconsin Kohl's General Merchandisers 53051 60,000
48 Corning New York Corning Electronics, Electrical Equip. 14831 56,300
49 Rolling Meadows Illinois Arthur J. Gallagher Diversified Financials 60008 56,000
50 Moline Illinois Deere Construction and Farm Machinery 61265 55,500
51 Northbrook Illinois Allstate Insurance: Property and Casualty (Stock) 60062 55,200
52 North Chicago Illinois AbbVie Pharmaceuticals 60064 55,000
53 Des Peres Missouri Edward Jones Securities 63131 55,000
54 Evendale Ohio General Electric Aerospace & Defense 45215 53,000
55 Portage Michigan Stryker Medical Products and Equipment 49002 53,000
56 Franklin Tennessee Community Health Systems Health Care: Medical Facilities 37067 52,500
57 Secaucus New Jersey Quest Diagnostics Health Care: Pharmacy and Other Services 07094 50,500
58 Reno Nevada Caesars Entertainment Hotels, Casinos, Resorts 89501 50,000
59 New Britain Connecticut Stanley Black & Decker Industrial Machinery 06053 48,500
60 Dublin Ohio Cardinal Health Wholesalers: Health Care 43017 48,400
61 Palm Beach Gardens Florida Carrier Global Industrial Machinery 33418 48,000
62 Boise Idaho Micron Technology Semiconductors and Other Electronic Components 83716 48,000
63 Burlington New Jersey Burlington Stores Specialty Retailers: Apparel 08016 47,300
64 Melbourne Florida L3Harris Technologies Aerospace & Defense 32919 47,000
65 Antioch Tennessee LKQ Wholesalers: Diversified 37013 47,000
66 Glenview Illinois Illinois Tool Works Industrial Machinery 60025 44,000
67 Benton Harbor Michigan Whirlpool Electronics, Electrical Equip. 49022 44,000
68 Conshohocken Pennsylvania Cencora Wholesalers: Health Care 19428 44,000
69 Evansville Indiana Berry Global Packaging, Containers 47710 42,000
70 Calhoun Georgia Mohawk Industries Home Equipment, Furnishings 30701 41,900
71 Las Vegas Nevada Las Vegas Sands Hotels, Casinos, Resorts 89113 40,100
72 Bolingbrook Illinois Ulta Beauty Specialty Retailers: Other 60440 39,000
73 Sumner Washington Lululemon athletica Specialty Retailers: Apparel 98390 39,000
74 Auburn Hills Michigan BorgWarner Motor Vehicles & Parts 48326 38,300
75 Deerfield Illinois Baxter International Medical Products and Equipment 60015 38,000
76 Coraopolis Pennsylvania Dick's Sporting Goods Specialty Retailers: Other 15108 37,400
77 Memphis Tennessee International Paper Packaging, Containers 38197 37,000
78 Palo Alto California Broadcom Semiconductors and Other Electronic Components 94304 37,000
79 Midland Michigan Dow Chemicals 48674 36,000
80 Purchase New York Mastercard Financial Data Services 10577 35,300
81 Mentor Ohio Avery Dennison Packaging, Containers 44060 35,000
82 Newport News Virginia Ferguson Wholesalers: Diversified 23606 35,000
83 Princeton New Jersey Bristol-Myers Squibb Pharmaceuticals 08543 34,100
84 Lowell Arkansas J.B. Hunt Transport Services Trucking, Truck Leasing 72745 33,600
85 Ankeny Iowa Casey's General Stores Specialty Retailers: Other 50021 33,100
86 Marlborough Massachusetts BJ's Wholesale Club General Merchandisers 01752 33,000
87 Westlake Texas Charles Schwab Securities 76262 32,100
88 Canonsburg Pennsylvania Viatris Pharmaceuticals 15317 32,000
89 Coral Gables Florida MasTec Engineering & Construction 33134 32,000
90 Louisville Kentucky Yum Brands Food Services 40213 31,700
91 Westerville Ohio Vertiv s Electronics, Electrical Equip. 43082 31,000
92 Medford Oregon Lithia Motors Automotive Retailing, Services 97501 30,200
93 Rosemont Illinois US Foods Wholesalers: Food and Grocery 60018 30,000
94 Burlington Massachusetts Keurig Dr Pepper Beverages 01803 29,400
95 Bloomfield Hills Michigan Penske Automotive Automotive Retailing, Services 48302 28,900
96 Thousand Oaks California Amgen Pharmaceuticals 91320 28,000
97 Irvine California Ingram Micro Wholesalers: Electronics and Office Equipment 92612 26,100
98 Estero Florida Hertz Automotive Retailing, Services 33928 26,000
99 Fort Lauderdale Florida AutoNation Automotive Retailing, Services 33301 25,100
100 Melville New York Henry Schein Wholesalers: Health Care 11747 25,000
101 Monroe Louisiana Lumen Technologies Telecommunications 71203 25,000
102 Norwalk Connecticut Booking s Internet Services and Retailing 06854 24,200
103 Mountain View California Intuit Computer Software 94043 24,200
104 Wilmington Massachusetts Analog Devices Semiconductors and Other Electronic Components 01887 24,000
105 Wilmington Delaware DuPont Chemicals 19805 24,000
106 Downers Grove Illinois Dover Industrial Machinery 60515 24,000
107 Elkhart Indiana THOR Industries Motor Vehicles & Parts 46514 22,300
108 Buffalo New York M&T Bank Commercial Banks 14203 22,100
109 Maplewood Minnesota Solventum Medical Products and Equipment 55144 22,000
110 Indianapolis Indiana Corteva Food Production 46268 22,000
111 Summit New Jersey Kenvue Household and Personal Products 07901 22,000
112 Glen Allen Virginia Markel Insurance: Property and Casualty (Stock) 23060 22,000
113 Centennial Colorado Arrow Electronics Wholesalers: Electronics and Office Equipment 80112 21,500
114 Riverwoods Illinois Discover Financial Diversified Financials 60015 21,000
115 Winona Minnesota Fastenal Wholesalers: Diversified 55987 21,000
116 Pleasanton California Workday Computer Software 94588 20,500
117 Austin Minnesota Hormel Foods Food Consumer Products 55912 20,000
118 Stamford Connecticut Synchrony Financial Diversified Financials 06902 20,000
119 Des Moines Iowa Principal Financial Insurance: Life, Health (Stock) 50392 19,700
120 Hershey Pennsylvania Hershey Food Consumer Products 17033 19,300
121 Hartford Connecticut Hartford Insurance Insurance: Property and Casualty (Stock) 06155 19,100
122 St. Petersburg Florida Raymond James Financial Securities 33716 19,000
123 Bellevue Washington Expeditors International of Washington Transportation and Logistics 98006 18,900
124 Oshkosh Wisconsin Oshkosh Construction and Farm Machinery 54902 18,500
125 Findlay Ohio Marathon Petroleum Petroleum Refining 45840 18,300
126 Long Beach California Molina Healthcare Health Care: Insurance and Managed Care 90802 18,000
127 Plantation Florida Chewy Internet Services and Retailing 33322 18,000
128 Livonia Michigan Masco Home Equipment, Furnishings 48152 18,000
129 Jacksonville Florida GuideWell Mutual Insurance: Life, Health (Stock) 32246 17,900
130 Foster City California Gilead Sciences Pharmaceuticals 94404 17,600
131 Tempe Arizona Carvana Automotive Retailing, Services 85281 17,400
132 Fremont California Lam Research Semiconductors and Other Electronic Components 94538 17,400
133 Raleigh North Carolina First Citizens BancShares Commercial Banks 27609 17,300
134 Providence Rhode Island Citizens Financial Commercial Banks 02903 17,300
135 Warsaw Indiana Zimmer Biomet s Medical Products and Equipment 46580 17,000
136 Juno Beach Florida NextEra Energy Utilities: Gas and Electric 33408 16,800
137 Cleveland Ohio TransDigm Aerospace & Defense 44115 16,600
138 Seattle Washington Expedia Internet Services and Retailing 98119 16,500
139 Columbus Ohio American Electric Power Utilities: Gas and Electric 43215 16,300
140 Westminster Colorado Ball Packaging, Containers 80021 16,000
141 Sunnyvale California Intuitive Surgical Medical Products and Equipment 94086 15,600
142 Phoenix Arizona Avnet Wholesalers: Electronics and Office Equipment 85034 15,500
143 Lake Forest Illinois Packaging Corp. of America Packaging, Containers 60045 15,400
144 Santa Clara California Palo Alto Networks Network and Other Communications Equipment 95054 15,300
145 Vernon Hills Illinois CDW Information Technology Services 60061 15,100
146 Manhattan Beach California Skechers U.S.A. Apparel 90266 15,100
147 Tarrytown New York Regeneron Pharmaceuticals Pharmaceuticals 10591 15,100
148 Milpitas California KLA Semiconductors and Other Electronic Components 95035 15,100
149 Byron Center Michigan SpartanNash Wholesalers: Food and Grocery 49315 15,000
150 Duluth Georgia Asbury Automotive Automotive Retailing, Services 30097 15,000
151 Sunny Isles Beach Florida Icahn Enterprises Diversified Financials 33160 15,000
152 Arlington Texas D.R. Horton Homebuilders 76011 14,800
153 Camden New Jersey Campbell's Food Consumer Products 08103 14,400
154 Chandler Arizona Insight Enterprises Information Technology Services 85286 14,300
155 Baltimore Maryland Constellation Energy Energy 21231 14,200
156 Rosemead California Edison International Utilities: Gas and Electric 91770 14,000
157 Merriam Kansas Seaboard Food Production 66202 14,000
158 Kingsport Tennessee Eastman Chemical Chemicals 37660 14,000
159 Los Gatos California Netflix Entertainment 95032 14,000
160 Pittsburgh Pennsylvania Alcoa Metals 15212 13,900
161 Tampa Florida Mosaic Chemicals 33602 13,800
162 Eden Prairie Minnesota C.H. Robinson Worldwide Transportation and Logistics 55347 13,800
163 Englewood Colorado EchoStar Telecommunications 80112 13,700
164 Redwood City California Equinix Real Estate 94065 13,600
165 Newark New Jersey Public Service Enterprise Utilities: Gas and Electric 07102 13,000
166 Fort Wayne Indiana Steel Dynamics Metals 46804 13,000
167 Columbus Georgia Aflac Insurance: Life, Health (Stock) 31999 12,700
168 Oak Brook Illinois Ace Hardware Wholesalers: Diversified 60523 12,500
169 Akron Ohio FirstEnergy Utilities: Gas and Electric 44308 12,300
170 New Orleans Louisiana Entergy Utilities: Gas and Electric 70113 12,300
171 Birmingham Alabama Vulcan Materials Building Materials, Glass 35242 12,000
172 El Dorado Arkansas Murphy USA Specialty Retailers: Other 71730 11,600
173 Oakland California Block Financial Data Services 94612 11,400
174 Westchester Illinois Ingredion Food Production 60154 11,200
175 Madison Wisconsin American Family Insurance Insurance: Property and Casualty (Stock) 53783 11,100
176 Chattanooga Tennessee Unum Insurance: Life, Health (Stock) 37402 10,900
177 Long Island City New York Altice USA Telecommunications 11101 10,900
178 Charlotte North Carolina Sonic Automotive Automotive Retailing, Services 28211 10,800
179 Springfield Massachusetts Eversource Energy Utilities: Gas and Electric 01104 10,700
180 Inver Grove Heights Minnesota CHS Food Production 55077 10,700
181 San Mateo California Franklin Resources Securities 94403 10,200
182 Beverly Hills California Endeavor Entertainment 90210 10,000
183 San Antonio Texas Valero Energy Petroleum Refining 78249 9,900
184 Woodland Hills California Farmers Insurance Exchange Insurance: Property and Casualty (Mutual) 91367 9,900
185 Radnor Pennsylvania Lincoln National Insurance: Life, Health (Stock) 19087 9,800
186 Detroit Michigan DTE Energy Utilities: Gas and Electric 48226 9,500
187 Chicago Illinois Old Republic International Insurance: Property and Casualty (Stock) 60601 9,400
188 Victor New York Constellation Brands Beverages 14564 9,300
189 Arlington Virginia AES Utilities: Gas and Electric 22203 9,100
190 Arden Hills Minnesota Land O'Lakes Food Consumer Products 55126 9,000
191 San Diego California LPL Financial s Securities 92121 9,000
192 Orrville Ohio J.M. Smucker Food Consumer Products 44667 9,000
193 Jackson Michigan CMS Energy Utilities: Gas and Electric 49201 8,300
194 Washington District of Columbia Fannie Mae Diversified Financials 20005 8,200
195 Herndon Virginia QXO Building Products Wholesalers: Diversified 20170 8,100
196 McLean Virginia Freddie Mac Diversified Financials 22102 8,100
197 New Braunfels Texas Rush Enterprises Automotive Retailing, Services 78130 7,900
198 Cambridge Massachusetts Biogen Pharmaceuticals 02142 7,600
199 Lansing Michigan Auto-Owners Insurance Insurance: Property and Casualty (Mutual) 48917 7,300
200 Milwaukee Wisconsin WEC Energy Utilities: Gas and Electric 53203 7,000
201 Reston Virginia NVR Homebuilders 20190 7,000
202 Atlanta Georgia Pulte Homebuilders 30326 6,800
203 Irving Texas Vistra Energy 75039 6,800
204 Erie Pennsylvania Erie Insurance Insurance: Property and Casualty (Mutual) 16530 6,700
205 Allentown Pennsylvania PPL Utilities: Gas and Electric 18101 6,700
206 Omaha Nebraska Mutual of Omaha Insurance Insurance: Life, Health (Mutual) 68175 6,500
207 Richmond Virginia Altria Tobacco 23230 6,200
208 Corona California Monster Beverage Beverages 92879 6,000
209 Johnston Rhode Island FM Insurance: Property and Casualty (Stock) 02919 5,800
210 San Jose California Super Micro Computer Computers, Office Equipment 95131 5,700
211 St. Louis Missouri Core & Main Wholesalers: Diversified 63146 5,700
212 St. Paul Minnesota Securian Financial Insurance: Life, Health (Stock) 55101 5,600
213 Fairfield Ohio Cincinnati Financial Insurance: Property and Casualty (Stock) 45014 5,600
214 Dallas Texas HF Sinclair Petroleum Refining 75219 5,300
215 Tulsa Oklahoma Oneok Pipelines 74103 5,200
216 Fort Washington Pennsylvania Toll Brothers Homebuilders 19034 4,900
217 Miami Florida World Kinect Energy 33178 4,700
218 Boston Massachusetts American Tower Real Estate 02116 4,700
219 Newport Beach California Pacific Life Insurance: Life, Health (Stock) 92660 4,300
220 Chesterfield Missouri Reinsurance of America Insurance: Life, Health (Stock) 63017 4,100
221 Minneapolis Minnesota Thrivent Financial for Lutherans Insurance: Life, Health (Mutual) 55415 4,000
222 Parsippany New Jersey PBF Energy Petroleum Refining 07054 3,900
223 Waltham Massachusetts Global Partners Energy 02453 3,800
224 Scottsdale Arizona Taylor Morrison Home Homebuilders 85251 3,000
225 Greenwich Connecticut Interactive Brokers Securities 06830 3,000
226 San Francisco California Prologis Real Estate 94111 2,700
227 Cincinnati Ohio Western & Southern Financial Insurance: Life, Health (Mutual) 45202 2,700
228 Oklahoma City Oklahoma Devon Energy Mining, Crude-Oil Production 73102 2,300
229 Maumee Ohio Andersons Food Production 43537 2,300
230 Midland Texas Diamondback Energy Mining, Crude-Oil Production 79701 2,000
231 Brentwood Tennessee Delek US Petroleum Refining 37027 2,000
232 New York New York Hess Mining, Crude-Oil Production 10036 1,800
233 Houston Texas Cheniere Energy Pipelines 77002 1,700
234 Denver Colorado Ovintiv Mining, Crude-Oil Production 80202 1,600
235 Toledo Ohio Welltower Real Estate 43615 700
236 El Segundo California A-Mark Precious Metals Wholesalers: Diversified 90245 500
In [183]:
# Join the Dataframe 'gdfusact' with 'dfminempco' for the Top 10
gdfusactminempco = gdfusact.merge(dfminempco, how = 'inner', on = ['Zip Code'])
gdfusactminempco = gdfusactminempco.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [184]:
mctminempco = gdfusactminempco.explore(column='Revenue (rounded)', name='Smallest Employer Company in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctminempco)
mctminempco
Out[184]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [185]:
# Check the Total Employee in each City
dfctte = df.groupby(['City','State'])[df.columns[[6]]].sum('Employees').sort_values('Employees', ascending=False)
dfctte
Out[185]:
Employees
City State
Seattle Washington 2101600
Bentonville Arkansas 2100000
New York New York 2028200
Atlanta Georgia 1233700
Chicago Illinois 724600
Cincinnati Ohio 593500
Dallas Texas 590100
Minneapolis Minnesota 573300
Memphis Tennessee 559900
Houston Texas 557600
San Francisco California 492000
Omaha Nebraska 463100
Newark California 450000
Philadelphia Pennsylvania 448700
Charlotte North Carolina 422700
Eden Prairie Minnesota 413800
Arlington Virginia 367100
Framingham Massachusetts 364000
Purchase New York 354300
Teaneck New Jersey 336800
Issaquah Washington 333000
Deerfield Illinois 290500
Irving Texas 287000
Austin Texas 284700
Armonk New York 284500
Bethesda Maryland 276000
McLean Virginia 275900
Nashville Tennessee 271000
Woonsocket Rhode Island 259500
Lakeland Florida 255000
Santa Clara California 250200
San Jose California 248200
Plano Texas 245500
Boise Idaho 244600
Redmond Washington 228000
Stamford Connecticut 225500
Reston Virginia 220000
Mooresville North Carolina 215500
Pittsburgh Pennsylvania 209800
Mountain View California 207500
Burbank California 205000
Goodlettsville Tennessee 194200
Orlando Florida 191100
Cleveland Ohio 188400
Detroit Michigan 182200
Greenwich Connecticut 179600
Southfield Michigan 173700
Indianapolis Indiana 172700
Dearborn Michigan 171000
Cupertino California 164000
St. Louis Missouri 160700
St. Petersburg Florida 157000
Chesapeake Virginia 139600
New Brunswick New Jersey 138100
Springdale Arkansas 138000
Newport Beach California 134800
Louisville Kentucky 134400
Fort Worth Texas 133300
Ashburn Virginia 130000
Waltham Massachusetts 128800
Wallingford Connecticut 125000
Denver Colorado 123800
Spring Texas 121900
Phoenix Arizona 121000
Boston Massachusetts 115500
St. Paul Minnesota 115100
Jacksonville Florida 114900
Abbott Park Illinois 114000
Las Vegas Nevada 109100
Round Rock Texas 108000
Dublin California 107000
Milwaukee Wisconsin 106900
Auburn Hills Michigan 100600
Richmond Virginia 99300
Falls Church Virginia 97000
Palo Alto California 95000
Washington District of Columbia 93200
Durham North Carolina 88000
King of Prussia Pennsylvania 87500
Marlborough Massachusetts 86000
Springfield Missouri 85600
Richfield Minnesota 85000
Cambridge Massachusetts 84400
Coral Gables Florida 82700
Akron Ohio 80300
Providence Rhode Island 79600
Beaverton Oregon 79400
Newport News Virginia 79000
San Diego California 74800
Menlo Park California 74100
Franklin Lakes New Jersey 74000
Rahway New Jersey 74000
Bloomfield Connecticut 72400
Farmington Connecticut 72000
Columbus Indiana 69600
Bloomington Illinois 67400
Mayfield Village Ohio 66300
Burlington North Carolina 65400
Raleigh North Carolina 65300
Norwalk Connecticut 64600
Roseland New Jersey 64000
Menomonee Falls Wisconsin 60000
Columbus Ohio 58700
Corning New York 56300
Rolling Meadows Illinois 56000
Moline Illinois 55500
Northbrook Illinois 55200
North Chicago Illinois 55000
Des Peres Missouri 55000
Portage Michigan 53000
Evendale Ohio 53000
Franklin Tennessee 52500
Newark New Jersey 50900
Secaucus New Jersey 50500
Reno Nevada 50000
Bellevue Washington 49000
New Britain Connecticut 48500
Dublin Ohio 48400
Palm Beach Gardens Florida 48000
San Antonio Texas 47900
Burlington New Jersey 47300
Antioch Tennessee 47000
Melbourne Florida 47000
Glen Allen Virginia 45200
Conshohocken Pennsylvania 44000
Benton Harbor Michigan 44000
Glenview Illinois 44000
Fremont California 43200
Evansville Indiana 42000
Maumee Ohio 41900
Calhoun Georgia 41900
Brentwood Tennessee 41000
Lake Forest Illinois 40400
Oakland California 39800
Sumner Washington 39000
Duluth Georgia 39000
Bolingbrook Illinois 39000
Parsippany New Jersey 38200
Coraopolis Pennsylvania 37400
Tampa Florida 36800
Chandler Arizona 36600
Midland Michigan 36000
Mentor Ohio 35000
Beverly Hills California 34200
Princeton New Jersey 34100
Lowell Arkansas 33600
Ankeny Iowa 33100
Englewood Colorado 32700
Westlake Texas 32100
Canonsburg Pennsylvania 32000
Birmingham Alabama 31600
Westerville Ohio 31000
Long Island City New York 30700
Medford Oregon 30200
Rosemont Illinois 30000
Burlington Massachusetts 29400
Allentown Pennsylvania 29100
Bloomfield Hills Michigan 28900
Thousand Oaks California 28000
Redwood City California 27300
Irvine California 26100
Estero Florida 26000
Toledo Ohio 25700
Miami Florida 25300
Fort Lauderdale Florida 25100
Melville New York 25000
Monroe Louisiana 25000
Wilmington Massachusetts 24000
Delaware 24000
Downers Grove Illinois 24000
Elkhart Indiana 22300
Buffalo New York 22100
Maplewood Minnesota 22000
Summit New Jersey 22000
Springfield Massachusetts 21900
Centennial Colorado 21500
Riverwoods Illinois 21000
Winona Minnesota 21000
Pleasanton California 20500
Austin Minnesota 20000
Des Moines Iowa 19700
Hershey Pennsylvania 19300
Hartford Connecticut 19100
Scottsdale Arizona 19000
Oshkosh Wisconsin 18500
Findlay Ohio 18300
Livonia Michigan 18000
Plantation Florida 18000
Long Beach California 18000
Foster City California 17600
Tempe Arizona 17400
Warsaw Indiana 17000
Juno Beach Florida 16800
Westminster Colorado 16000
Sunnyvale California 15600
Milpitas California 15100
Manhattan Beach California 15100
Vernon Hills Illinois 15100
Tarrytown New York 15100
Sunny Isles Beach Florida 15000
Byron Center Michigan 15000
Arlington Texas 14800
Camden New Jersey 14400
Baltimore Maryland 14200
Los Gatos California 14000
Merriam Kansas 14000
Kingsport Tennessee 14000
Rosemead California 14000
Fort Wayne Indiana 13000
Columbus Georgia 12700
Oak Brook Illinois 12500
New Orleans Louisiana 12300
El Dorado Arkansas 11600
Westchester Illinois 11200
Madison Wisconsin 11100
Tulsa Oklahoma 11000
Chattanooga Tennessee 10900
Inver Grove Heights Minnesota 10700
San Mateo California 10200
Woodland Hills California 9900
Radnor Pennsylvania 9800
Victor New York 9300
Orrville Ohio 9000
Arden Hills Minnesota 9000
Jackson Michigan 8300
Herndon Virginia 8100
New Braunfels Texas 7900
Lansing Michigan 7300
Erie Pennsylvania 6700
Corona California 6000
Johnston Rhode Island 5800
Fairfield Ohio 5600
Fort Washington Pennsylvania 4900
Chesterfield Missouri 4100
Oklahoma City Oklahoma 2300
Midland Texas 2000
El Segundo California 500
In [186]:
# Join the Dataframe 'gdfusact' with 'dfctte' for the Top 10
dfctte = dfctte.merge(df[['City','State','Company','Zip Code']], how = 'inner', on = ['City','State'])
gdfusactctte = gdfusact.merge(dfctte, how = 'inner', on = ['Zip Code'])
gdfusactctte = gdfusactctte.sort_values('Employees', ascending=False).reset_index(drop=True)
gdfusactctte
Out[186]:
Zip Code Latitude Longitude Population geometry City State Employees Company
0 98109 48 -122 32,552 POINT (-122.34486 47.63128) Seattle Washington 2101600 Amazon
1 98188 47 -122 26,769 POINT (-122.27398 47.44754) Seattle Washington 2101600 Alaska Air
2 98101 48 -122 16,396 POINT (-122.33454 47.61119) Seattle Washington 2101600 Nordstrom
3 98101 48 -122 16,396 POINT (-122.33454 47.61119) Seattle Washington 2101600 Coupang
4 98134 48 -122 779 POINT (-122.33686 47.57691) Seattle Washington 2101600 Starbucks
5 98119 48 -122 26,390 POINT (-122.36932 47.63943) Seattle Washington 2101600 Expedia
6 72712 36 -94 38,072 POINT (-94.22196 36.39837) Bentonville Arkansas 2100000 Walmart
7 10041 41 -74 6,217 POINT (-74.01 40.7031) New York New York 2028200 S&P Global
8 10006 41 -74 4,475 POINT (-74.01306 40.70949) New York New York 2028200 ABM Industries
9 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York New York 2028200 Omnicom
10 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York New York 2028200 Kyndryl s
11 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York New York 2028200 Travelers
12 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York New York 2028200 TIAA
13 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York New York 2028200 JPMorgan Chase
14 10013 41 -74 28,215 POINT (-74.00472 40.72001) New York New York 2028200 Oscar Health
15 10013 41 -74 28,215 POINT (-74.00472 40.72001) New York New York 2028200 Citi
16 10010 41 -74 31,905 POINT (-73.98243 40.73899) New York New York 2028200 New York Life Insurance
17 10003 41 -74 53,825 POINT (-73.98915 40.73184) New York New York 2028200 Consolidated Edison
18 10019 41 -74 44,276 POINT (-73.9853 40.76586) New York New York 2028200 Apollo Global Management
19 10003 41 -74 53,825 POINT (-73.98915 40.73184) New York New York 2028200 Warner Bros. Discovery
20 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York New York 2028200 Foot Locker
21 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York New York 2028200 Guardian Life
22 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York New York 2028200 BlackRock
23 10105 41 -74 0 POINT (-73.978 40.7644) New York New York 2028200 Equitable
24 10286 41 -74 5,269 POINT (-74.01182 40.7052) New York New York 2028200 Bank of New York
25 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York New York 2028200 Macy's
26 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York New York 2028200 PVH
27 10019 41 -74 44,276 POINT (-73.9853 40.76586) New York New York 2028200 Loews
28 10282 41 -74 5,960 POINT (-74.01495 40.71655) New York New York 2028200 Goldman Sachs
29 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York New York 2028200 Marsh & McLennan
30 10169 41 -74 0 POINT (-73.97643 40.75467) New York New York 2028200 Voya Financial
31 10169 41 -74 0 POINT (-73.97643 40.75467) New York New York 2028200 StoneX
32 10154 41 -74 0 POINT (-73.97249 40.75778) New York New York 2028200 Blackstone
33 10153 41 -74 0 POINT (-73.97244 40.76362) New York New York 2028200 Estée Lauder
34 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York New York 2028200 News Corp.
35 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York New York 2028200 Hess
36 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York New York 2028200 Fox
37 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York New York 2028200 Paramount Global
38 10019 41 -74 44,276 POINT (-73.9853 40.76586) New York New York 2028200 International Flavors & Fragrances
39 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York New York 2028200 Morgan Stanley
40 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York New York 2028200 Verizon
41 10022 41 -74 34,340 POINT (-73.96787 40.75856) New York New York 2028200 Jefferies Financial
42 10022 41 -74 34,340 POINT (-73.96787 40.75856) New York New York 2028200 Interpublic
43 10022 41 -74 34,340 POINT (-73.96787 40.75856) New York New York 2028200 Colgate-Palmolive
44 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York New York 2028200 KKR
45 10020 41 -74 0 POINT (-73.98071 40.75917) New York New York 2028200 American International
46 10020 41 -74 0 POINT (-73.98071 40.75917) New York New York 2028200 Sirius XM
47 10285 41 -74 0 POINT (-74.01492 40.71201) New York New York 2028200 American Express
48 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York New York 2028200 Pfizer
49 10166 41 -74 0 POINT (-73.9769 40.7531) New York New York 2028200 MetLife
50 30328 34 -84 38,821 POINT (-84.38617 33.93194) Atlanta Georgia 1233700 UPS
51 30339 34 -84 34,872 POINT (-84.46483 33.86786) Atlanta Georgia 1233700 Assurant
52 30339 34 -84 34,872 POINT (-84.46483 33.86786) Atlanta Georgia 1233700 Genuine Parts
53 30339 34 -84 34,872 POINT (-84.46483 33.86786) Atlanta Georgia 1233700 Home Depot
54 30328 34 -84 38,821 POINT (-84.38617 33.93194) Atlanta Georgia 1233700 Newell Brands
55 30328 34 -84 38,821 POINT (-84.38617 33.93194) Atlanta Georgia 1233700 Graphic Packaging
56 30328 34 -84 38,821 POINT (-84.38617 33.93194) Atlanta Georgia 1233700 Intercontinental Exchange
57 30354 34 -84 15,487 POINT (-84.38609 33.66058) Atlanta Georgia 1233700 Delta Airlines
58 30326 34 -84 8,497 POINT (-84.36342 33.84957) Atlanta Georgia 1233700 Global Payments
59 30313 34 -84 10,845 POINT (-84.39761 33.76369) Atlanta Georgia 1233700 Coca-Cola
60 30308 34 -84 23,329 POINT (-84.37773 33.77094) Atlanta Georgia 1233700 Norfolk Southern
61 30308 34 -84 23,329 POINT (-84.37773 33.77094) Atlanta Georgia 1233700 Southern
62 30326 34 -84 8,497 POINT (-84.36342 33.84957) Atlanta Georgia 1233700 Pulte
63 60603 42 -88 1,126 POINT (-87.6274 41.88018) Chicago Illinois 724600 Exelon
64 60661 42 -88 11,516 POINT (-87.64409 41.88291) Chicago Illinois 724600 Motorola Solutions
65 60661 42 -88 11,516 POINT (-87.64409 41.88291) Chicago Illinois 724600 GE HealthCare Technologies
66 60654 42 -88 24,303 POINT (-87.63673 41.89209) Chicago Illinois 724600 Conagra Brands
67 60654 42 -88 24,303 POINT (-87.63673 41.89209) Chicago Illinois 724600 Kellanova
68 60607 42 -88 30,197 POINT (-87.65175 41.87467) Chicago Illinois 724600 McDonald's
69 60607 42 -88 30,197 POINT (-87.65175 41.87467) Chicago Illinois 724600 Mondelez
70 60606 42 -88 3,527 POINT (-87.63724 41.88178) Chicago Illinois 724600 Molson Coors Beverage
71 60606 42 -88 3,527 POINT (-87.63724 41.88178) Chicago Illinois 724600 United Airlines
72 60603 42 -88 1,126 POINT (-87.6274 41.88018) Chicago Illinois 724600 Northern Trust
73 60601 42 -88 16,292 POINT (-87.62197 41.88527) Chicago Illinois 724600 Old Republic International
74 60601 42 -88 16,292 POINT (-87.62197 41.88527) Chicago Illinois 724600 Jones Lang LaSalle
75 60601 42 -88 16,292 POINT (-87.62197 41.88527) Chicago Illinois 724600 Archer Daniels Midland
76 60601 42 -88 16,292 POINT (-87.62197 41.88527) Chicago Illinois 724600 Kraft Heinz
77 45202 39 -85 17,022 POINT (-84.50243 39.10885) Cincinnati Ohio 593500 American Financial
78 45202 39 -85 17,022 POINT (-84.50243 39.10885) Cincinnati Ohio 593500 Western & Southern Financial
79 45202 39 -85 17,022 POINT (-84.50243 39.10885) Cincinnati Ohio 593500 Procter & Gamble
80 45202 39 -85 17,022 POINT (-84.50243 39.10885) Cincinnati Ohio 593500 Kroger
81 45262 39 -84 0 POINT (-84.4569 39.1616) Cincinnati Ohio 593500 Cintas
82 45263 39 -84 0 POINT (-84.4569 39.1616) Cincinnati Ohio 593500 Fifth Third Bancorp
83 75240 33 -97 24,718 POINT (-96.78924 32.93194) Dallas Texas 590100 AECOM
84 75254 33 -97 24,737 POINT (-96.80127 32.94571) Dallas Texas 590100 Tenet Healthcare
85 75243 33 -97 63,907 POINT (-96.73633 32.91232) Dallas Texas 590100 Texas Instruments
86 75201 33 -97 18,078 POINT (-96.79953 32.78826) Dallas Texas 590100 CBRE
87 75201 33 -97 18,078 POINT (-96.79953 32.78826) Dallas Texas 590100 Jacobs Solutions
88 75202 33 -97 2,744 POINT (-96.8037 32.77843) Dallas Texas 590100 AT&T
89 75219 33 -97 25,001 POINT (-96.81315 32.81087) Dallas Texas 590100 HF Sinclair
90 75225 33 -97 22,383 POINT (-96.79109 32.86511) Dallas Texas 590100 Energy Transfer
91 75235 33 -97 19,067 POINT (-96.84798 32.83219) Dallas Texas 590100 Southwest Airlines
92 55402 45 -93 760 POINT (-93.27119 44.97608) Minneapolis Minnesota 573300 U.S. Bancorp
93 55474 45 -93 28,071 POINT (-93.27 44.98) Minneapolis Minnesota 573300 Ameriprise Financial
94 55403 45 -93 17,354 POINT (-93.28588 44.97023) Minneapolis Minnesota 573300 Target
95 55415 45 -93 6,474 POINT (-93.2578 44.97463) Minneapolis Minnesota 573300 Thrivent Financial for Lutherans
96 55426 45 -93 25,451 POINT (-93.38139 44.95635) Minneapolis Minnesota 573300 General Mills
97 55401 45 -93 11,526 POINT (-93.26984 44.98526) Minneapolis Minnesota 573300 Xcel Energy
98 38103 35 -90 14,025 POINT (-90.05518 35.15308) Memphis Tennessee 559900 AutoZone
99 38120 35 -90 13,249 POINT (-89.85237 35.12344) Memphis Tennessee 559900 FedEx
100 38197 35 -90 0 POINT (-90.0487 35.1497) Memphis Tennessee 559900 International Paper
101 77008 30 -95 40,155 POINT (-95.41766 29.79856) Houston Texas 557600 Quanta Services
102 77002 30 -95 19,616 POINT (-95.36538 29.75635) Houston Texas 557600 KBR
103 77002 30 -95 19,616 POINT (-95.36538 29.75635) Houston Texas 557600 CenterPoint Energy
104 77002 30 -95 19,616 POINT (-95.36538 29.75635) Houston Texas 557600 NRG Energy
105 77002 30 -95 19,616 POINT (-95.36538 29.75635) Houston Texas 557600 Chevron
106 77002 30 -95 19,616 POINT (-95.36538 29.75635) Houston Texas 557600 Cheniere Energy
107 77002 30 -95 19,616 POINT (-95.36538 29.75635) Houston Texas 557600 Targa Resources
108 77002 30 -95 19,616 POINT (-95.36538 29.75635) Houston Texas 557600 Waste Management
109 77002 30 -95 19,616 POINT (-95.36538 29.75635) Houston Texas 557600 EOG Resources
110 77002 30 -95 19,616 POINT (-95.36538 29.75635) Houston Texas 557600 Plains GP
111 77002 30 -95 19,616 POINT (-95.36538 29.75635) Houston Texas 557600 Kinder Morgan
112 77002 30 -95 19,616 POINT (-95.36538 29.75635) Houston Texas 557600 Enterprise Products Partners
113 77056 30 -95 23,314 POINT (-95.46806 29.74849) Houston Texas 557600 Westlake
114 77024 30 -96 37,647 POINT (-95.50869 29.77073) Houston Texas 557600 1 Automotive
115 77024 30 -96 37,647 POINT (-95.50869 29.77073) Houston Texas 557600 Par Pacific
116 77032 30 -95 13,536 POINT (-95.34004 29.96523) Houston Texas 557600 Halliburton
117 77042 30 -96 40,725 POINT (-95.56015 29.74125) Houston Texas 557600 Phillips 66
118 77042 30 -96 40,725 POINT (-95.56015 29.74125) Houston Texas 557600 APA
119 77042 30 -96 40,725 POINT (-95.56015 29.74125) Houston Texas 557600 NOV
120 77046 30 -95 1,873 POINT (-95.43301 29.73438) Houston Texas 557600 Occidental Petroleum
121 77019 30 -95 23,662 POINT (-95.41212 29.75318) Houston Texas 557600 Corebridge Financial
122 77077 30 -96 63,421 POINT (-95.64189 29.75375) Houston Texas 557600 Sysco
123 77079 30 -96 35,540 POINT (-95.6037 29.77632) Houston Texas 557600 ConocoPhillips
124 77079 30 -96 35,540 POINT (-95.6037 29.77632) Houston Texas 557600 Baker Hughes
125 94158 38 -122 11,206 POINT (-122.39153 37.77116) San Francisco California 492000 Uber
126 94111 38 -122 4,553 POINT (-122.3998 37.79847) San Francisco California 492000 Prologis
127 94107 38 -122 30,190 POINT (-122.39508 37.76473) San Francisco California 492000 DoorDash
128 94105 38 -122 14,890 POINT (-122.39707 37.79239) San Francisco California 492000 Visa
129 94104 38 -122 478 POINT (-122.40211 37.79144) San Francisco California 492000 Wells Fargo
130 94105 38 -122 14,890 POINT (-122.39707 37.79239) San Francisco California 492000 Salesforce
131 94105 38 -122 14,890 POINT (-122.39707 37.79239) San Francisco California 492000 Gap
132 94109 38 -122 54,397 POINT (-122.42138 37.79334) San Francisco California 492000 Williams-Sonoma
133 94103 38 -122 33,524 POINT (-122.41136 37.77299) San Francisco California 492000 Airbnb
134 68179 41 -96 0 POINT (-95.9352 41.2597) Omaha Nebraska 463100 Union Pacific
135 68131 41 -96 13,928 POINT (-95.96479 41.26435) Omaha Nebraska 463100 Berkshire Hathaway
136 68102 41 -96 9,311 POINT (-95.93224 41.26231) Omaha Nebraska 463100 Peter Kiewit Sons'
137 68175 41 -96 0 POINT (-95.96584 41.26502) Omaha Nebraska 463100 Mutual of Omaha Insurance
138 94560 38 -122 47,145 POINT (-122.02523 37.50771) Newark California 450000 Concentrix
139 19103 40 -75 25,602 POINT (-75.17386 39.95303) Philadelphia Pennsylvania 448700 Comcast
140 19103 40 -75 25,602 POINT (-75.17386 39.95303) Philadelphia Pennsylvania 448700 Aramark
141 28202 35 -81 16,855 POINT (-80.8447 35.22773) Charlotte North Carolina 422700 Honeywell
142 28255 35 -81 0 POINT (-80.8434 35.2267) Charlotte North Carolina 422700 Bank of America
143 28211 35 -81 32,637 POINT (-80.79604 35.16816) Charlotte North Carolina 422700 Sonic Automotive
144 28211 35 -81 32,637 POINT (-80.79604 35.16816) Charlotte North Carolina 422700 Nucor
145 28202 35 -81 16,855 POINT (-80.8447 35.22773) Charlotte North Carolina 422700 Truist Financial
146 28202 35 -81 16,855 POINT (-80.8447 35.22773) Charlotte North Carolina 422700 Duke Energy
147 55347 45 -93 30,467 POINT (-93.46638 44.82931) Eden Prairie Minnesota 413800 C.H. Robinson Worldwide
148 55344 45 -93 14,180 POINT (-93.43037 44.86452) Eden Prairie Minnesota 413800 UnitedHealth
149 22209 39 -77 13,725 POINT (-77.07309 38.89413) Arlington Virginia 367100 RTX
150 22203 39 -77 25,921 POINT (-77.1164 38.87377) Arlington Virginia 367100 AES
151 22202 39 -77 27,352 POINT (-77.05175 38.8569) Arlington Virginia 367100 Boeing
152 01701 42 -71 32,270 POINT (-71.43796 42.32195) Framingham Massachusetts 364000 TJX
153 10577 41 -74 5,901 POINT (-73.71349 41.03755) Purchase New York 354300 PepsiCo
154 10577 41 -74 5,901 POINT (-73.71349 41.03755) Purchase New York 354300 Mastercard
155 07666 41 -74 41,499 POINT (-74.01067 40.88998) Teaneck New Jersey 336800 Cognizant Technology
156 98027 48 -122 28,335 POINT (-122.00176 47.50387) Issaquah Washington 333000 Costco
157 60015 42 -88 27,720 POINT (-87.87486 42.17239) Deerfield Illinois 290500 Walgreens
158 60015 42 -88 27,720 POINT (-87.87486 42.17239) Deerfield Illinois 290500 Baxter International
159 75039 33 -97 22,450 POINT (-96.94042 32.88592) Irving Texas 287000 Fluor
160 75039 33 -97 22,450 POINT (-96.94042 32.88592) Irving Texas 287000 McKesson
161 75038 33 -97 33,097 POINT (-96.97946 32.87231) Irving Texas 287000 Kimberly-Clark
162 75039 33 -97 22,450 POINT (-96.94042 32.88592) Irving Texas 287000 Commercial Metals
163 75039 33 -97 22,450 POINT (-96.94042 32.88592) Irving Texas 287000 Celanese
164 75039 33 -97 22,450 POINT (-96.94042 32.88592) Irving Texas 287000 Caterpillar
165 75039 33 -97 22,450 POINT (-96.94042 32.88592) Irving Texas 287000 Builders FirstSource
166 75039 33 -97 22,450 POINT (-96.94042 32.88592) Irving Texas 287000 Vistra
167 78725 30 -98 10,810 POINT (-97.60859 30.23554) Austin Texas 284700 Tesla
168 78741 30 -98 45,274 POINT (-97.71389 30.23007) Austin Texas 284700 Oracle
169 10504 41 -74 7,853 POINT (-73.70629 41.13065) Armonk New York 284500 IBM
170 20814 39 -77 30,822 POINT (-77.10295 39.00506) Bethesda Maryland 276000 Marriott International
171 20817 39 -77 37,738 POINT (-77.14919 38.99809) Bethesda Maryland 276000 Lockheed Martin
172 22102 39 -77 28,577 POINT (-77.22901 38.95199) McLean Virginia 275900 Capital One
173 22102 39 -77 28,577 POINT (-77.22901 38.95199) McLean Virginia 275900 Booz Allen Hamilton
174 22102 39 -77 28,577 POINT (-77.22901 38.95199) McLean Virginia 275900 Freddie Mac
175 22102 39 -77 28,577 POINT (-77.22901 38.95199) McLean Virginia 275900 Hilton
176 37203 36 -87 20,234 POINT (-86.78986 36.14937) Nashville Tennessee 271000 HCA Healthcare
177 02895 42 -71 43,081 POINT (-71.49923 42.00103) Woonsocket Rhode Island 259500 CVS Health
178 33811 28 -82 28,456 POINT (-82.01866 27.97933) Lakeland Florida 255000 Publix Super Markets
179 95054 37 -122 25,196 POINT (-121.96483 37.39308) Santa Clara California 250200 Applied Materials
180 95054 37 -122 25,196 POINT (-121.96483 37.39308) Santa Clara California 250200 Intel
181 95051 37 -122 61,345 POINT (-121.98444 37.3483) Santa Clara California 250200 Nvidia
182 95054 37 -122 25,196 POINT (-121.96483 37.39308) Santa Clara California 250200 Advanced Micro Devices
183 95054 37 -122 25,196 POINT (-121.96483 37.39308) Santa Clara California 250200 Palo Alto Networks
184 95054 37 -122 25,196 POINT (-121.96483 37.39308) Santa Clara California 250200 ServiceNow
185 95131 37 -122 30,745 POINT (-121.89793 37.38729) San Jose California 248200 Super Micro Computer
186 95110 37 -122 19,444 POINT (-121.9097 37.34656) San Jose California 248200 Adobe
187 95131 37 -122 30,745 POINT (-121.89793 37.38729) San Jose California 248200 PayPal
188 95134 37 -122 30,255 POINT (-121.94528 37.43003) San Jose California 248200 Sanmina
189 95119 37 -122 10,449 POINT (-121.79077 37.22756) San Jose California 248200 Western Digital
190 95134 37 -122 30,255 POINT (-121.94528 37.43003) San Jose California 248200 Cisco Systems
191 95125 37 -122 53,934 POINT (-121.89408 37.29554) San Jose California 248200 Ebay
192 75074 33 -97 53,146 POINT (-96.67304 33.03298) Plano Texas 245500 Yum China s
193 83706 44 -116 36,183 POINT (-116.19427 43.59108) Boise Idaho 244600 Albertsons
194 83716 44 -116 21,091 POINT (-115.6548 43.67271) Boise Idaho 244600 Micron Technology
195 98052 48 -122 79,074 POINT (-122.1203 47.68148) Redmond Washington 228000 Microsoft
196 06901 41 -74 10,506 POINT (-73.53845 41.05349) Stamford Connecticut 225500 Philip Morris
197 06902 41 -74 72,915 POINT (-73.54751 41.05949) Stamford Connecticut 225500 Synchrony Financial
198 06902 41 -74 72,915 POINT (-73.54751 41.05949) Stamford Connecticut 225500 United Rentals
199 06902 41 -74 72,915 POINT (-73.54751 41.05949) Stamford Connecticut 225500 Charter Communications
200 20190 39 -77 22,092 POINT (-77.33806 38.95968) Reston Virginia 220000 NVR
201 20190 39 -77 22,092 POINT (-77.33806 38.95968) Reston Virginia 220000 Leidos s
202 20190 39 -77 22,092 POINT (-77.33806 38.95968) Reston Virginia 220000 General Dynamics
203 20190 39 -77 22,092 POINT (-77.33806 38.95968) Reston Virginia 220000 CACI International
204 20190 39 -77 22,092 POINT (-77.33806 38.95968) Reston Virginia 220000 Science Applications International
205 28117 36 -81 48,170 POINT (-80.89658 35.57405) Mooresville North Carolina 215500 Lowe's
206 15222 40 -80 5,649 POINT (-79.9912 40.44998) Pittsburgh Pennsylvania 209800 PNC
207 15219 40 -80 11,010 POINT (-79.98443 40.44304) Pittsburgh Pennsylvania 209800 United States Steel
208 15219 40 -80 11,010 POINT (-79.98443 40.44304) Pittsburgh Pennsylvania 209800 WESCO International
209 15212 40 -80 27,600 POINT (-80.00844 40.47106) Pittsburgh Pennsylvania 209800 Howmet Aerospace
210 15212 40 -80 27,600 POINT (-80.00844 40.47106) Pittsburgh Pennsylvania 209800 Westinghouse Air Brake Technologies
211 15212 40 -80 27,600 POINT (-80.00844 40.47106) Pittsburgh Pennsylvania 209800 Alcoa
212 15272 40 -80 2,481 POINT (-80.0048 40.44246) Pittsburgh Pennsylvania 209800 PPG Industries
213 94043 37 -122 32,042 POINT (-122.06892 37.41188) Mountain View California 207500 Intuit
214 94043 37 -122 32,042 POINT (-122.06892 37.41188) Mountain View California 207500 Alphabet
215 91521 34 -118 11,049 POINT (-118.3252 34.1569) Burbank California 205000 Walt Disney
216 37072 36 -87 32,344 POINT (-86.74494 36.35686) Goodlettsville Tennessee 194200 Dollar General
217 32837 28 -81 49,889 POINT (-81.41998 28.38074) Orlando Florida 191100 Darden Restaurants
218 44115 41 -82 10,389 POINT (-81.66999 41.49211) Cleveland Ohio 188400 TransDigm
219 44115 41 -82 10,389 POINT (-81.66999 41.49211) Cleveland Ohio 188400 Sherwin-Williams
220 44124 41 -81 40,046 POINT (-81.46774 41.49999) Cleveland Ohio 188400 Parker-Hannifin
221 44114 42 -82 7,472 POINT (-81.67625 41.5137) Cleveland Ohio 188400 KeyCorp
222 44114 42 -82 7,472 POINT (-81.67625 41.5137) Cleveland Ohio 188400 Cleveland-Cliffs
223 48265 42 -83 4,503 POINT (-83.0456 42.3317) Detroit Michigan 182200 General Motors
224 48226 42 -83 6,893 POINT (-83.05034 42.33182) Detroit Michigan 182200 DTE Energy
225 48226 42 -83 6,893 POINT (-83.05034 42.33182) Detroit Michigan 182200 Ally Financial
226 06831 41 -74 14,656 POINT (-73.66078 41.08782) Greenwich Connecticut 179600 GXO Logistics
227 06831 41 -74 14,656 POINT (-73.66078 41.08782) Greenwich Connecticut 179600 XPO
228 06830 41 -74 24,919 POINT (-73.624 41.048) Greenwich Connecticut 179600 W.R. Berkley
229 06830 41 -74 24,919 POINT (-73.624 41.048) Greenwich Connecticut 179600 Interactive Brokers
230 48033 42 -83 16,900 POINT (-83.28812 42.46478) Southfield Michigan 173700 Lear
231 46204 40 -86 11,022 POINT (-86.15703 39.77134) Indianapolis Indiana 172700 Elevance Health
232 46285 40 -86 0 POINT (-86.1582 39.7683) Indianapolis Indiana 172700 Eli Lilly
233 46268 40 -86 25,623 POINT (-86.23253 39.89769) Indianapolis Indiana 172700 Corteva
234 48126 42 -83 52,075 POINT (-83.18678 42.32999) Dearborn Michigan 171000 Ford Motor
235 95014 37 -122 61,109 POINT (-122.07981 37.30827) Cupertino California 164000 Apple
236 63144 39 -90 9,580 POINT (-90.3482 38.61943) St. Louis Missouri 160700 Post s
237 63136 39 -90 41,314 POINT (-90.25979 38.74418) St. Louis Missouri 160700 Emerson Electric
238 63105 39 -90 18,860 POINT (-90.32812 38.64427) St. Louis Missouri 160700 Graybar Electric
239 63105 39 -90 18,860 POINT (-90.32812 38.64427) St. Louis Missouri 160700 Centene
240 63146 39 -90 30,917 POINT (-90.47634 38.70135) St. Louis Missouri 160700 Core & Main
241 33716 28 -83 18,995 POINT (-82.65119 27.8774) St. Petersburg Florida 157000 Raymond James Financial
242 33716 28 -83 18,995 POINT (-82.65119 27.8774) St. Petersburg Florida 157000 Jabil
243 23320 37 -76 59,626 POINT (-76.21807 36.75208) Chesapeake Virginia 139600 Dollar Tree
244 72762 36 -94 47,402 POINT (-94.22794 36.18747) Springdale Arkansas 138000 Tyson Foods
245 92660 34 -118 34,788 POINT (-117.87504 33.63375) Newport Beach California 134800 Chipotle Mexican Grill
246 92660 34 -118 34,788 POINT (-117.87504 33.63375) Newport Beach California 134800 Pacific Life
247 40213 38 -86 15,805 POINT (-85.71571 38.177) Louisville Kentucky 134400 Yum Brands
248 40222 38 -86 21,634 POINT (-85.61173 38.26436) Louisville Kentucky 134400 BrightSpring Health Services
249 40202 38 -86 7,109 POINT (-85.75205 38.25288) Louisville Kentucky 134400 Humana
250 76155 33 -97 6,301 POINT (-97.04911 32.82404) Fort Worth Texas 133300 American Airlines
251 20147 39 -77 67,007 POINT (-77.47958 39.04151) Ashburn Virginia 130000 DXC Technology
252 02453 42 -71 30,314 POINT (-71.24101 42.36918) Waltham Massachusetts 128800 Global Partners
253 02451 42 -71 18,153 POINT (-71.2573 42.39859) Waltham Massachusetts 128800 Thermo Fisher Scientific
254 06492 41 -73 44,099 POINT (-72.80473 41.45927) Wallingford Connecticut 125000 Amphenol
255 80202 40 -105 18,233 POINT (-104.99768 39.75156) Denver Colorado 123800 VF
256 80202 40 -105 18,233 POINT (-104.99768 39.75156) Denver Colorado 123800 Ovintiv
257 80202 40 -105 18,233 POINT (-104.99768 39.75156) Denver Colorado 123800 DaVita
258 80237 40 -105 22,764 POINT (-104.90178 39.63996) Denver Colorado 123800 Newmont
259 77389 30 -96 44,545 POINT (-95.50752 30.11509) Spring Texas 121900 Exxon Mobil
260 77389 30 -96 44,545 POINT (-95.50752 30.11509) Spring Texas 121900 Hewlett Packard
261 85054 34 -112 10,159 POINT (-111.94763 33.67515) Phoenix Arizona 121000 Sprouts Farmers Market
262 85054 34 -112 10,159 POINT (-111.94763 33.67515) Phoenix Arizona 121000 Republic Services
263 85034 33 -112 4,825 POINT (-112.01989 33.43465) Phoenix Arizona 121000 Avnet
264 85004 33 -112 11,178 POINT (-112.06988 33.45159) Phoenix Arizona 121000 Freeport-McMoRan
265 02114 42 -71 13,853 POINT (-71.06686 42.36337) Boston Massachusetts 115500 State Street
266 02116 42 -71 22,040 POINT (-71.07638 42.35105) Boston Massachusetts 115500 American Tower
267 02210 42 -71 6,554 POINT (-71.03942 42.34815) Boston Massachusetts 115500 Vertex Pharmaceuticals
268 02116 42 -71 22,040 POINT (-71.07638 42.35105) Boston Massachusetts 115500 Liberty Mutual Insurance
269 02116 42 -71 22,040 POINT (-71.07638 42.35105) Boston Massachusetts 115500 Wayfair
270 55102 45 -93 19,565 POINT (-93.12149 44.93216) St. Paul Minnesota 115100 Ecolab
271 55101 45 -93 7,937 POINT (-93.08739 44.95111) St. Paul Minnesota 115100 Securian Financial
272 55144 45 -93 11,636 POINT (-93.04758 44.92912) St. Paul Minnesota 115100 3M
273 32202 30 -82 6,550 POINT (-81.64786 30.32505) Jacksonville Florida 114900 Fidelity National Information
274 32202 30 -82 6,550 POINT (-81.64786 30.32505) Jacksonville Florida 114900 CSX
275 32204 30 -82 8,421 POINT (-81.68095 30.31636) Jacksonville Florida 114900 Fidelity National Financial
276 32246 30 -82 60,443 POINT (-81.51782 30.29422) Jacksonville Florida 114900 GuideWell Mutual
277 60064 42 -88 15,047 POINT (-87.86122 42.3237) Abbott Park Illinois 114000 Abbott Laboratories
278 89113 36 -115 37,313 POINT (-115.26236 36.06017) Las Vegas Nevada 109100 Las Vegas Sands
279 89109 36 -115 6,924 POINT (-115.16327 36.12603) Las Vegas Nevada 109100 MGM Resorts International
280 78682 30 -98 0 POINT (-97.7273 30.4076) Round Rock Texas 108000 Dell Technologies
281 94568 38 -122 70,542 POINT (-121.90113 37.71596) Dublin California 107000 Ross Stores
282 53204 43 -88 40,008 POINT (-87.92552 43.01806) Milwaukee Wisconsin 106900 Rockwell Automation
283 53202 43 -88 26,269 POINT (-87.89893 43.04561) Milwaukee Wisconsin 106900 Northwestern Mutual
284 53203 43 -88 2,077 POINT (-87.91603 43.03828) Milwaukee Wisconsin 106900 Fiserv
285 53203 43 -88 2,077 POINT (-87.91603 43.03828) Milwaukee Wisconsin 106900 WEC Energy
286 53212 43 -88 29,099 POINT (-87.90845 43.07464) Milwaukee Wisconsin 106900 Manpower
287 48326 43 -83 24,488 POINT (-83.2531 42.67536) Auburn Hills Michigan 100600 Autoliv
288 48326 43 -83 24,488 POINT (-83.2531 42.67536) Auburn Hills Michigan 100600 BorgWarner
289 23238 38 -78 25,893 POINT (-77.64138 37.59595) Richmond Virginia 99300 Performance Food
290 23238 38 -78 25,893 POINT (-77.64138 37.59595) Richmond Virginia 99300 CarMax
291 23227 38 -77 25,574 POINT (-77.44234 37.61486) Richmond Virginia 99300 ARKO
292 23230 38 -77 8,304 POINT (-77.49153 37.587) Richmond Virginia 99300 Altria
293 23219 38 -77 3,856 POINT (-77.43484 37.54076) Richmond Virginia 99300 Dominion Energy
294 22042 39 -77 34,631 POINT (-77.19406 38.86463) Falls Church Virginia 97000 Northrop Grumman
295 94304 37 -122 4,731 POINT (-122.16699 37.39744) Palo Alto California 95000 HP
296 94304 37 -122 4,731 POINT (-122.16699 37.39744) Palo Alto California 95000 Broadcom
297 20037 39 -77 12,441 POINT (-77.0535 38.89213) Washington District of Columbia 93200 Danaher
298 20005 39 -77 12,960 POINT (-77.0316 38.90443) Washington District of Columbia 93200 Fannie Mae
299 20003 39 -77 36,194 POINT (-76.99033 38.88193) Washington District of Columbia 93200 Xylem
300 27703 36 -79 62,994 POINT (-78.80452 35.96299) Durham North Carolina 88000 IQVIA s
301 19406 40 -75 29,388 POINT (-75.38402 40.09467) King of Prussia Pennsylvania 87500 Universal Health Services
302 01752 42 -72 41,398 POINT (-71.54681 42.3494) Marlborough Massachusetts 86000 BJ's Wholesale Club
303 01752 42 -72 41,398 POINT (-71.54681 42.3494) Marlborough Massachusetts 86000 Boston Scientific
304 65802 37 -93 46,005 POINT (-93.35167 37.21048) Springfield Missouri 85600 O'Reilly Automotive
305 55423 45 -93 36,779 POINT (-93.28144 44.87663) Richfield Minnesota 85000 Best Buy
306 02141 42 -71 14,677 POINT (-71.08218 42.37041) Cambridge Massachusetts 84400 GE Vernova
307 02142 42 -71 4,349 POINT (-71.08189 42.36295) Cambridge Massachusetts 84400 Biogen
308 33134 26 -80 36,937 POINT (-80.2712 25.75338) Coral Gables Florida 82700 MasTec
309 33134 26 -80 36,937 POINT (-80.2712 25.75338) Coral Gables Florida 82700 Ryder System
310 44316 41 -81 0 POINT (-81.47083 41.07854) Akron Ohio 80300 Goodyear Tire & Rubber
311 44308 41 -82 1,261 POINT (-81.51751 41.0818) Akron Ohio 80300 FirstEnergy
312 02908 42 -71 39,661 POINT (-71.43926 41.83877) Providence Rhode Island 79600 United Natural Foods
313 02903 42 -71 12,309 POINT (-71.41003 41.81902) Providence Rhode Island 79600 Citizens Financial
314 02903 42 -71 12,309 POINT (-71.41003 41.81902) Providence Rhode Island 79600 Textron
315 97005 45 -123 27,812 POINT (-122.80397 45.49144) Beaverton Oregon 79400 Nike
316 23606 37 -76 29,899 POINT (-76.49557 37.07847) Newport News Virginia 79000 Ferguson
317 23607 37 -76 23,028 POINT (-76.42235 36.98753) Newport News Virginia 79000 Huntington Ingalls Industries
318 92121 33 -117 4,157 POINT (-117.20231 32.8973) San Diego California 74800 Qualcomm
319 92121 33 -117 4,157 POINT (-117.20231 32.8973) San Diego California 74800 LPL Financial s
320 92101 33 -117 48,163 POINT (-117.18589 32.7162) San Diego California 74800 Sempra
321 94025 37 -122 40,230 POINT (-122.1829 37.45087) Menlo Park California 74100 Meta
322 07417 41 -74 11,035 POINT (-74.20836 41.00859) Franklin Lakes New Jersey 74000 Becton Dickinson
323 07065 41 -74 29,748 POINT (-74.28066 40.60765) Rahway New Jersey 74000 Merck
324 06002 42 -73 21,547 POINT (-72.73714 41.84286) Bloomfield Connecticut 72400 Cigna
325 06032 42 -73 18,642 POINT (-72.83147 41.72528) Farmington Connecticut 72000 Otis Worldwide
326 47201 39 -86 48,602 POINT (-85.99432 39.15074) Columbus Indiana 69600 Cummins
327 61710 41 -89 79,633 POINT (-88.9894 40.516) Bloomington Illinois 67400 State Farm
328 44143 42 -81 24,337 POINT (-81.47513 41.55358) Mayfield Village Ohio 66300 Progressive
329 27215 36 -79 45,967 POINT (-79.48729 36.03055) Burlington North Carolina 65400 Labcorp s
330 27609 36 -79 35,548 POINT (-78.63282 35.8437) Raleigh North Carolina 65300 First Citizens BancShares
331 27609 36 -79 35,548 POINT (-78.63282 35.8437) Raleigh North Carolina 65300 Advance Auto Parts
332 06851 41 -73 28,591 POINT (-73.40387 41.13948) Norwalk Connecticut 64600 EMCOR
333 06854 41 -73 31,753 POINT (-73.42972 41.09148) Norwalk Connecticut 64600 Booking s
334 07068 41 -74 6,211 POINT (-74.30862 40.82077) Roseland New Jersey 64000 Automatic Data Processing
335 53051 43 -88 39,000 POINT (-88.12348 43.14905) Menomonee Falls Wisconsin 60000 Kohl's
336 43287 40 -83 905,748 POINT (-83.0011 39.9619) Columbus Ohio 58700 Huntington Bancshares
337 43215 40 -83 16,999 POINT (-83.01262 39.96633) Columbus Ohio 58700 American Electric Power
338 43215 40 -83 16,999 POINT (-83.01262 39.96633) Columbus Ohio 58700 Nationwide
339 14831 42 -77 5,986 POINT (-77.0553 42.1429) Corning New York 56300 Corning
340 60008 42 -88 22,949 POINT (-88.0229 42.0739) Rolling Meadows Illinois 56000 Arthur J. Gallagher
341 61265 41 -90 43,851 POINT (-90.48895 41.48195) Moline Illinois 55500 Deere
342 60062 42 -88 41,667 POINT (-87.84235 42.12663) Northbrook Illinois 55200 Allstate
343 60064 42 -88 15,047 POINT (-87.86122 42.3237) North Chicago Illinois 55000 AbbVie
344 63131 39 -90 17,993 POINT (-90.44365 38.6172) Des Peres Missouri 55000 Edward Jones
345 45215 39 -84 30,806 POINT (-84.46221 39.23536) Evendale Ohio 53000 General Electric
346 49002 42 -86 19,444 POINT (-85.55906 42.19867) Portage Michigan 53000 Stryker
347 37067 36 -87 31,550 POINT (-86.77461 35.91314) Franklin Tennessee 52500 Community Health Systems
348 07102 41 -74 12,954 POINT (-74.17343 40.73576) Newark New Jersey 50900 Public Service Enterprise
349 07102 41 -74 12,954 POINT (-74.17343 40.73576) Newark New Jersey 50900 Prudential Financial
350 07094 41 -74 21,437 POINT (-74.06588 40.78109) Secaucus New Jersey 50500 Quest Diagnostics
351 89501 40 -120 3,641 POINT (-119.81262 39.52602) Reno Nevada 50000 Caesars Entertainment
352 98006 48 -122 40,770 POINT (-122.14957 47.55772) Bellevue Washington 49000 Expeditors International of Washington
353 98004 48 -122 39,435 POINT (-122.20548 47.61865) Bellevue Washington 49000 Paccar
354 06053 42 -73 35,697 POINT (-72.7941 41.68874) New Britain Connecticut 48500 Stanley Black & Decker
355 43017 40 -83 41,422 POINT (-83.13314 40.1189) Dublin Ohio 48400 Cardinal Health
356 33418 27 -80 42,979 POINT (-80.16641 26.86077) Palm Beach Gardens Florida 48000 Carrier Global
357 78288 29 -98 0 POINT (-98.4935 29.4239) San Antonio Texas 47900 USAA
358 78249 30 -99 61,772 POINT (-98.614 29.56752) San Antonio Texas 47900 Valero Energy
359 08016 40 -75 34,801 POINT (-74.83198 40.06926) Burlington New Jersey 47300 Burlington Stores
360 32919 28 -81 0 POINT (-80.6386 28.0909) Melbourne Florida 47000 L3Harris Technologies
361 37013 36 -87 102,055 POINT (-86.63445 36.04658) Antioch Tennessee 47000 LKQ
362 23060 38 -78 36,111 POINT (-77.53427 37.65981) Glen Allen Virginia 45200 Owens & Minor
363 23060 38 -78 36,111 POINT (-77.53427 37.65981) Glen Allen Virginia 45200 Markel
364 19428 40 -75 20,225 POINT (-75.30317 40.08011) Conshohocken Pennsylvania 44000 Cencora
365 60025 42 -88 40,877 POINT (-87.81204 42.07466) Glenview Illinois 44000 Illinois Tool Works
366 49022 42 -86 29,796 POINT (-86.3675 42.11434) Benton Harbor Michigan 44000 Whirlpool
367 94538 38 -122 67,704 POINT (-121.96361 37.50653) Fremont California 43200 TD Synnex
368 94538 38 -122 67,704 POINT (-121.96361 37.50653) Fremont California 43200 Lam Research
369 47710 38 -88 18,802 POINT (-87.57618 38.02518) Evansville Indiana 42000 Berry Global
370 43537 42 -84 29,639 POINT (-83.68542 41.57433) Maumee Ohio 41900 Andersons
371 30701 34 -85 43,078 POINT (-84.95385 34.49535) Calhoun Georgia 41900 Mohawk Industries
372 43537 42 -84 29,639 POINT (-83.68542 41.57433) Maumee Ohio 41900 Dana
373 37027 36 -87 61,961 POINT (-86.78439 35.99978) Brentwood Tennessee 41000 Tractor Supply
374 37027 36 -87 61,961 POINT (-86.78439 35.99978) Brentwood Tennessee 41000 Delek US
375 60045 42 -88 20,957 POINT (-87.87006 42.23807) Lake Forest Illinois 40400 Packaging Corp. of America
376 60045 42 -88 20,957 POINT (-87.87006 42.23807) Lake Forest Illinois 40400 W.W. Grainger
377 94612 38 -122 17,663 POINT (-122.2662 37.80789) Oakland California 39800 Block
378 94612 38 -122 17,663 POINT (-122.2662 37.80789) Oakland California 39800 PG&E
379 60440 42 -88 52,074 POINT (-88.07572 41.70125) Bolingbrook Illinois 39000 Ulta Beauty
380 30097 34 -84 45,543 POINT (-84.14702 34.0271) Duluth Georgia 39000 Asbury Automotive
381 30096 34 -84 71,141 POINT (-84.14791 33.97691) Duluth Georgia 39000 AGCO
382 98390 47 -122 11,497 POINT (-122.22894 47.21195) Sumner Washington 39000 Lululemon athletica
383 07054 41 -74 30,139 POINT (-74.40239 40.85527) Parsippany New Jersey 38200 PBF Energy
384 07054 41 -74 30,139 POINT (-74.40239 40.85527) Parsippany New Jersey 38200 Zoetis
385 07054 41 -74 30,139 POINT (-74.40239 40.85527) Parsippany New Jersey 38200 Avis Budget
386 15108 41 -80 42,782 POINT (-80.20031 40.50006) Coraopolis Pennsylvania 37400 Dick's Sporting Goods
387 33637 28 -82 17,785 POINT (-82.36118 28.04715) Tampa Florida 36800 Crown s
388 33602 28 -82 19,694 POINT (-82.45675 27.95371) Tampa Florida 36800 Mosaic
389 85224 33 -112 48,304 POINT (-111.87616 33.32351) Chandler Arizona 36600 Microchip Technology
390 85286 33 -112 49,870 POINT (-111.83156 33.27146) Chandler Arizona 36600 Insight Enterprises
391 48674 44 -84 42,547 POINT (-84.23229 43.70732) Midland Michigan 36000 Dow
392 44060 42 -81 60,257 POINT (-81.32806 41.67742) Mentor Ohio 35000 Avery Dennison
393 90210 34 -118 19,652 POINT (-118.41505 34.10251) Beverly Hills California 34200 Endeavor
394 90210 34 -118 19,652 POINT (-118.41505 34.10251) Beverly Hills California 34200 Live Nation Entertainment
395 08543 40 -75 30,681 POINT (-74.65804 40.34899) Princeton New Jersey 34100 Bristol-Myers Squibb
396 72745 36 -94 14,521 POINT (-94.10046 36.2477) Lowell Arkansas 33600 J.B. Hunt Transport Services
397 50021 42 -94 29,718 POINT (-93.56838 41.7207) Ankeny Iowa 33100 Casey's General Stores
398 80112 40 -105 36,687 POINT (-104.85854 39.57288) Englewood Colorado 32700 EchoStar
399 80112 40 -105 36,687 POINT (-104.85854 39.57288) Englewood Colorado 32700 QVC
400 76262 33 -97 43,589 POINT (-97.22101 33.01137) Westlake Texas 32100 Charles Schwab
401 15317 40 -80 43,813 POINT (-80.16535 40.27105) Canonsburg Pennsylvania 32000 Viatris
402 35203 34 -87 3,301 POINT (-86.80999 33.51847) Birmingham Alabama 31600 Regions Financial
403 35242 33 -87 56,956 POINT (-86.67073 33.42371) Birmingham Alabama 31600 Vulcan Materials
404 43082 40 -83 33,799 POINT (-82.88437 40.15537) Westerville Ohio 31000 Vertiv s
405 11101 41 -74 39,007 POINT (-73.93916 40.74679) Long Island City New York 30700 JetBlue Airways
406 11101 41 -74 39,007 POINT (-73.93916 40.74679) Long Island City New York 30700 Altice USA
407 97501 42 -123 45,008 POINT (-122.89459 42.2856) Medford Oregon 30200 Lithia Motors
408 60018 42 -88 29,302 POINT (-87.89846 41.99629) Rosemont Illinois 30000 US Foods
409 01803 43 -71 26,068 POINT (-71.20147 42.5028) Burlington Massachusetts 29400 Keurig Dr Pepper
410 18106 41 -76 6,437 POINT (-75.59542 40.57472) Allentown Pennsylvania 29100 Air Products & Chemicals
411 18101 41 -75 5,789 POINT (-75.4698 40.60301) Allentown Pennsylvania 29100 PPL
412 48302 43 -83 17,346 POINT (-83.29608 42.5849) Bloomfield Hills Michigan 28900 Penske Automotive
413 91320 34 -119 43,628 POINT (-118.94795 34.17339) Thousand Oaks California 28000 Amgen
414 94065 38 -122 11,620 POINT (-122.24683 37.53504) Redwood City California 27300 Electronic Arts
415 94065 38 -122 11,620 POINT (-122.24683 37.53504) Redwood City California 27300 Equinix
416 92612 34 -118 33,706 POINT (-117.82457 33.65984) Irvine California 26100 Ingram Micro
417 33928 26 -82 30,786 POINT (-81.71002 26.43545) Estero Florida 26000 Hertz
418 43659 42 -84 0 POINT (-83.5554 41.6639) Toledo Ohio 25700 Owens Corning
419 43615 42 -84 40,813 POINT (-83.67255 41.65045) Toledo Ohio 25700 Welltower
420 33178 26 -80 65,515 POINT (-80.4213 25.83578) Miami Florida 25300 World Kinect
421 33126 26 -80 47,038 POINT (-80.30054 25.78061) Miami Florida 25300 Lennar
422 33133 26 -80 34,651 POINT (-80.24327 25.72983) Miami Florida 25300 Watsco
423 33301 26 -80 17,831 POINT (-80.12745 26.12128) Fort Lauderdale Florida 25100 AutoNation
424 11747 41 -73 19,826 POINT (-73.40931 40.78372) Melville New York 25000 Henry Schein
425 71203 33 -92 38,770 POINT (-92.01351 32.58398) Monroe Louisiana 25000 Lumen Technologies
426 19805 40 -76 40,315 POINT (-75.59373 39.74523) Wilmington Delaware 24000 DuPont
427 60515 42 -88 29,045 POINT (-88.0247 41.80991) Downers Grove Illinois 24000 Dover
428 01887 43 -71 23,195 POINT (-71.16541 42.56091) Wilmington Massachusetts 24000 Analog Devices
429 46514 42 -86 41,480 POINT (-85.97547 41.72328) Elkhart Indiana 22300 THOR Industries
430 14203 43 -79 2,526 POINT (-78.86507 42.86244) Buffalo New York 22100 M&T Bank
431 07901 41 -74 24,502 POINT (-74.36604 40.71462) Summit New Jersey 22000 Kenvue
432 55144 45 -93 11,636 POINT (-93.04758 44.92912) Maplewood Minnesota 22000 Solventum
433 01111 42 -73 0 POINT (-72.54793 42.11733) Springfield Massachusetts 21900 Mass Mutual
434 01104 42 -73 21,745 POINT (-72.56733 42.13326) Springfield Massachusetts 21900 Eversource Energy
435 80112 40 -105 36,687 POINT (-104.85854 39.57288) Centennial Colorado 21500 Arrow Electronics
436 60015 42 -88 27,720 POINT (-87.87486 42.17239) Riverwoods Illinois 21000 Discover Financial
437 55987 44 -92 33,911 POINT (-91.63143 43.98469) Winona Minnesota 21000 Fastenal
438 94588 38 -122 34,423 POINT (-121.88178 37.73801) Pleasanton California 20500 Workday
439 55912 44 -93 29,438 POINT (-92.99148 43.6827) Austin Minnesota 20000 Hormel Foods
440 50392 42 -94 15,018 POINT (-93.628 41.5898) Des Moines Iowa 19700 Principal Financial
441 17033 40 -77 17,009 POINT (-76.62754 40.26829) Hershey Pennsylvania 19300 Hershey
442 06155 42 -73 121,054 POINT (-72.6859 41.7638) Hartford Connecticut 19100 Hartford Insurance
443 85251 33 -112 39,976 POINT (-111.92025 33.49406) Scottsdale Arizona 19000 Taylor Morrison Home
444 85254 34 -112 46,655 POINT (-111.95176 33.61474) Scottsdale Arizona 19000 Reliance
445 54902 44 -89 21,982 POINT (-88.53969 43.94934) Oshkosh Wisconsin 18500 Oshkosh
446 45840 41 -84 54,342 POINT (-83.64943 41.02626) Findlay Ohio 18300 Marathon Petroleum
447 90802 34 -118 39,859 POINT (-118.21143 33.75035) Long Beach California 18000 Molina Healthcare
448 33322 26 -80 40,522 POINT (-80.27429 26.14997) Plantation Florida 18000 Chewy
449 48152 42 -83 30,394 POINT (-83.37433 42.42597) Livonia Michigan 18000 Masco
450 94404 38 -122 35,950 POINT (-122.26905 37.5562) Foster City California 17600 Gilead Sciences
451 85281 33 -112 70,726 POINT (-111.93157 33.42805) Tempe Arizona 17400 Carvana
452 46580 41 -86 21,812 POINT (-85.87212 41.20884) Warsaw Indiana 17000 Zimmer Biomet s
453 33408 27 -80 18,766 POINT (-80.05677 26.84115) Juno Beach Florida 16800 NextEra Energy
454 80021 40 -105 35,562 POINT (-105.11448 39.89105) Westminster Colorado 16000 Ball
455 94086 37 -122 48,956 POINT (-122.02316 37.37164) Sunnyvale California 15600 Intuitive Surgical
456 95035 37 -122 78,479 POINT (-121.87632 37.44319) Milpitas California 15100 KLA
457 90266 34 -118 34,584 POINT (-118.39705 33.88968) Manhattan Beach California 15100 Skechers U.S.A.
458 10591 41 -74 23,663 POINT (-73.84653 41.08436) Tarrytown New York 15100 Regeneron Pharmaceuticals
459 60061 42 -88 27,883 POINT (-87.96046 42.2334) Vernon Hills Illinois 15100 CDW
460 33160 26 -80 43,225 POINT (-80.13583 25.93234) Sunny Isles Beach Florida 15000 Icahn Enterprises
461 49315 43 -86 26,123 POINT (-85.73589 42.80101) Byron Center Michigan 15000 SpartanNash
462 76011 33 -97 22,297 POINT (-97.08223 32.7543) Arlington Texas 14800 D.R. Horton
463 08103 40 -75 13,137 POINT (-75.11275 39.93533) Camden New Jersey 14400 Campbell's
464 21231 39 -77 14,556 POINT (-76.592 39.28775) Baltimore Maryland 14200 Constellation Energy
465 37660 37 -83 40,114 POINT (-82.57339 36.52938) Kingsport Tennessee 14000 Eastman Chemical
466 66202 39 -95 17,321 POINT (-94.66909 39.02392) Merriam Kansas 14000 Seaboard
467 91770 34 -118 58,893 POINT (-118.08361 34.06395) Rosemead California 14000 Edison International
468 95032 37 -122 27,682 POINT (-121.92359 37.20859) Los Gatos California 14000 Netflix
469 46804 41 -85 29,177 POINT (-85.23913 41.05421) Fort Wayne Indiana 13000 Steel Dynamics
470 31999 32 -85 3,469 POINT (-84.98772 32.46078) Columbus Georgia 12700 Aflac
471 60523 42 -88 10,012 POINT (-87.95406 41.83713) Oak Brook Illinois 12500 Ace Hardware
472 70113 30 -90 9,888 POINT (-90.08382 29.9422) New Orleans Louisiana 12300 Entergy
473 71730 33 -93 29,187 POINT (-92.63458 33.20303) El Dorado Arkansas 11600 Murphy USA
474 60154 42 -88 16,524 POINT (-87.88986 41.84923) Westchester Illinois 11200 Ingredion
475 53783 43 -89 0 POINT (-89.4012 43.0731) Madison Wisconsin 11100 American Family Insurance
476 74172 36 -96 0 POINT (-95.9905 36.1544) Tulsa Oklahoma 11000 Williams
477 74103 36 -96 2,419 POINT (-95.9957 36.15617) Tulsa Oklahoma 11000 Oneok
478 37402 35 -85 4,203 POINT (-85.31553 35.04672) Chattanooga Tennessee 10900 Unum
479 55077 45 -93 14,585 POINT (-93.07574 44.81989) Inver Grove Heights Minnesota 10700 CHS
480 94403 38 -122 43,459 POINT (-122.30454 37.53844) San Mateo California 10200 Franklin Resources
481 91367 34 -119 45,427 POINT (-118.61518 34.17708) Woodland Hills California 9900 Farmers Insurance Exchange
482 19087 40 -75 33,770 POINT (-75.40004 40.06172) Radnor Pennsylvania 9800 Lincoln National
483 14564 43 -77 16,257 POINT (-77.42417 42.98329) Victor New York 9300 Constellation Brands
484 55126 45 -93 27,484 POINT (-93.13581 45.08614) Arden Hills Minnesota 9000 Land O'Lakes
485 44667 41 -82 13,688 POINT (-81.76495 40.83386) Orrville Ohio 9000 J.M. Smucker
486 49201 42 -84 49,114 POINT (-84.38301 42.25213) Jackson Michigan 8300 CMS Energy
487 20170 39 -77 43,372 POINT (-77.38042 38.98075) Herndon Virginia 8100 QXO Building Products
488 78130 30 -98 95,787 POINT (-98.06877 29.69224) New Braunfels Texas 7900 Rush Enterprises
489 48917 43 -85 32,029 POINT (-84.63897 42.72509) Lansing Michigan 7300 Auto-Owners Insurance
490 16530 42 -80 94,831 POINT (-80.08204 42.13039) Erie Pennsylvania 6700 Erie Insurance
491 92879 34 -118 48,756 POINT (-117.5357 33.87979) Corona California 6000 Monster Beverage
492 02919 42 -72 29,473 POINT (-71.52002 41.82733) Johnston Rhode Island 5800 FM
493 45014 39 -85 45,652 POINT (-84.5521 39.32822) Fairfield Ohio 5600 Cincinnati Financial
494 19034 40 -75 7,084 POINT (-75.20953 40.13353) Fort Washington Pennsylvania 4900 Toll Brothers
495 63017 39 -91 43,074 POINT (-90.53722 38.65143) Chesterfield Missouri 4100 Reinsurance of America
496 73102 35 -98 3,590 POINT (-97.5191 35.47065) Oklahoma City Oklahoma 2300 Devon Energy
497 79701 32 -102 27,678 POINT (-102.08105 31.99239) Midland Texas 2000 Diamondback Energy
498 90245 34 -118 16,863 POINT (-118.40161 33.91709) El Segundo California 500 A-Mark Precious Metals
In [187]:
mctte = gdfusactctte.explore(column='Employees', name='Total Employees in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctte)
mctte
Out[187]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [188]:
# Check Average Number of Employee in each City
dfctavremp = df.groupby(['City','State'])[df.columns[[6]]].mean('Employees').sort_values('Employees', ascending=False)
dfctavremp
Out[188]:
Employees
City State
Bentonville Arkansas 2,100,000
Newark California 450,000
Framingham Massachusetts 364,000
Seattle Washington 350,267
Teaneck New Jersey 336,800
Issaquah Washington 333,000
Armonk New York 284,500
Nashville Tennessee 271,000
Woonsocket Rhode Island 259,500
Lakeland Florida 255,000
Plano Texas 245,500
Redmond Washington 228,000
Philadelphia Pennsylvania 224,350
Mooresville North Carolina 215,500
Eden Prairie Minnesota 206,900
Burbank California 205,000
Goodlettsville Tennessee 194,200
Orlando Florida 191,100
Memphis Tennessee 186,633
Purchase New York 177,150
Southfield Michigan 173,700
Dearborn Michigan 171,000
Cupertino California 164,000
Deerfield Illinois 145,250
Austin Texas 142,350
Chesapeake Virginia 139,600
New Brunswick New Jersey 138,100
Bethesda Maryland 138,000
Springdale Arkansas 138,000
Fort Worth Texas 133,300
Ashburn Virginia 130,000
Wallingford Connecticut 125,000
Arlington Virginia 122,367
Boise Idaho 122,300
Omaha Nebraska 115,775
Abbott Park Illinois 114,000
Round Rock Texas 108,000
Dublin California 107,000
Mountain View California 103,750
Cincinnati Ohio 98,917
Falls Church Virginia 97,000
Minneapolis Minnesota 95,550
Atlanta Georgia 94,900
Durham North Carolina 88,000
King of Prussia Pennsylvania 87,500
Springfield Missouri 85,600
Richfield Minnesota 85,000
Beaverton Oregon 79,400
St. Petersburg Florida 78,500
Menlo Park California 74,100
Rahway New Jersey 74,000
Franklin Lakes New Jersey 74,000
Bloomfield Connecticut 72,400
Farmington Connecticut 72,000
Charlotte North Carolina 70,450
Columbus Indiana 69,600
McLean Virginia 68,975
Newport Beach California 67,400
Bloomington Illinois 67,400
Mayfield Village Ohio 66,300
Dallas Texas 65,567
Burlington North Carolina 65,400
Waltham Massachusetts 64,400
Roseland New Jersey 64,000
Spring Texas 60,950
Detroit Michigan 60,733
Menomonee Falls Wisconsin 60,000
Indianapolis Indiana 57,567
Stamford Connecticut 56,375
Corning New York 56,300
Rolling Meadows Illinois 56,000
Moline Illinois 55,500
Northbrook Illinois 55,200
North Chicago Illinois 55,000
Des Peres Missouri 55,000
San Francisco California 54,667
Las Vegas Nevada 54,550
Portage Michigan 53,000
Evendale Ohio 53,000
Franklin Tennessee 52,500
Chicago Illinois 51,757
Secaucus New Jersey 50,500
Auburn Hills Michigan 50,300
Reno Nevada 50,000
New Britain Connecticut 48,500
Dublin Ohio 48,400
Palm Beach Gardens Florida 48,000
Palo Alto California 47,500
Burlington New Jersey 47,300
New York New York 47,167
Melbourne Florida 47,000
Antioch Tennessee 47,000
Greenwich Connecticut 44,900
Louisville Kentucky 44,800
Benton Harbor Michigan 44,000
Glenview Illinois 44,000
Reston Virginia 44,000
Conshohocken Pennsylvania 44,000
Marlborough Massachusetts 43,000
Cambridge Massachusetts 42,200
Evansville Indiana 42,000
Calhoun Georgia 41,900
Santa Clara California 41,700
Coral Gables Florida 41,350
Akron Ohio 40,150
Newport News Virginia 39,500
Bolingbrook Illinois 39,000
Sumner Washington 39,000
St. Paul Minnesota 38,367
Cleveland Ohio 37,680
Coraopolis Pennsylvania 37,400
Midland Michigan 36,000
Irving Texas 35,875
San Jose California 35,457
Mentor Ohio 35,000
Princeton New Jersey 34,100
Lowell Arkansas 33,600
Ankeny Iowa 33,100
Raleigh North Carolina 32,650
Norwalk Connecticut 32,300
St. Louis Missouri 32,140
Westlake Texas 32,100
Canonsburg Pennsylvania 32,000
Washington District of Columbia 31,067
Westerville Ohio 31,000
Denver Colorado 30,950
Phoenix Arizona 30,250
Medford Oregon 30,200
Rosemont Illinois 30,000
Pittsburgh Pennsylvania 29,971
Burlington Massachusetts 29,400
Bloomfield Hills Michigan 28,900
Jacksonville Florida 28,725
Thousand Oaks California 28,000
Providence Rhode Island 26,533
Irvine California 26,100
Estero Florida 26,000
Newark New Jersey 25,450
Fort Lauderdale Florida 25,100
Melville New York 25,000
Monroe Louisiana 25,000
San Diego California 24,933
Bellevue Washington 24,500
Downers Grove Illinois 24,000
Wilmington Massachusetts 24,000
Delaware 24,000
San Antonio Texas 23,950
Houston Texas 23,233
Boston Massachusetts 23,100
Glen Allen Virginia 22,600
Elkhart Indiana 22,300
Buffalo New York 22,100
Maplewood Minnesota 22,000
Summit New Jersey 22,000
Fremont California 21,600
Centennial Colorado 21,500
Milwaukee Wisconsin 21,380
Winona Minnesota 21,000
Riverwoods Illinois 21,000
Maumee Ohio 20,950
Brentwood Tennessee 20,500
Pleasanton California 20,500
Lake Forest Illinois 20,200
Austin Minnesota 20,000
Oakland California 19,900
Richmond Virginia 19,860
Des Moines Iowa 19,700
Columbus Ohio 19,567
Duluth Georgia 19,500
Hershey Pennsylvania 19,300
Hartford Connecticut 19,100
Oshkosh Wisconsin 18,500
Tampa Florida 18,400
Chandler Arizona 18,300
Findlay Ohio 18,300
Livonia Michigan 18,000
Plantation Florida 18,000
Long Beach California 18,000
Foster City California 17,600
Tempe Arizona 17,400
Beverly Hills California 17,100
Warsaw Indiana 17,000
Juno Beach Florida 16,800
Englewood Colorado 16,350
Westminster Colorado 16,000
Birmingham Alabama 15,800
Sunnyvale California 15,600
Long Island City New York 15,350
Tarrytown New York 15,100
Vernon Hills Illinois 15,100
Milpitas California 15,100
Manhattan Beach California 15,100
Byron Center Michigan 15,000
Sunny Isles Beach Florida 15,000
Arlington Texas 14,800
Allentown Pennsylvania 14,550
Camden New Jersey 14,400
Baltimore Maryland 14,200
Rosemead California 14,000
Kingsport Tennessee 14,000
Los Gatos California 14,000
Merriam Kansas 14,000
Redwood City California 13,650
Fort Wayne Indiana 13,000
Toledo Ohio 12,850
Parsippany New Jersey 12,733
Columbus Georgia 12,700
Oak Brook Illinois 12,500
New Orleans Louisiana 12,300
El Dorado Arkansas 11,600
Westchester Illinois 11,200
Madison Wisconsin 11,100
Springfield Massachusetts 10,950
Chattanooga Tennessee 10,900
Inver Grove Heights Minnesota 10,700
San Mateo California 10,200
Woodland Hills California 9,900
Radnor Pennsylvania 9,800
Scottsdale Arizona 9,500
Victor New York 9,300
Arden Hills Minnesota 9,000
Orrville Ohio 9,000
Miami Florida 8,433
Jackson Michigan 8,300
Herndon Virginia 8,100
New Braunfels Texas 7,900
Lansing Michigan 7,300
Erie Pennsylvania 6,700
Corona California 6,000
Johnston Rhode Island 5,800
Fairfield Ohio 5,600
Tulsa Oklahoma 5,500
Fort Washington Pennsylvania 4,900
Chesterfield Missouri 4,100
Oklahoma City Oklahoma 2,300
Midland Texas 2,000
El Segundo California 500
In [189]:
# Join the Dataframe 'gdfusact' with 'dfctavremp' for the Top 10
dfctavremp = dfctavremp.merge(df[['City','State','Company','Zip Code']], how = 'inner', on = ['City','State'])
gdfusactctavremp = gdfusact.merge(dfctavremp, how = 'inner', on = ['Zip Code'])
gdfusactctavremp = gdfusactctavremp.sort_values('Employees', ascending=False).reset_index(drop=True)
In [190]:
mctavremp = gdfusactctavremp.explore(column='Employees', name='Average Number of Employees in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctavremp)
mctavremp
Out[190]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [191]:
# Check the Most Efficient Company in each City
dfctmaxeffco = df.head(1)
dfctmaxeffco.insert(0, 'Efficiency', 1) # Add new Column 'Efficiency' to new

for ct in ctslist[0:]:
    dfct = df.where(df['City'] == ct[0]).where(df['State'] == ct[1]).dropna()
    dfct['Efficiency'] = dfct['Revenue (rounded)']/dfct['Employees']
    dfctmaxeffco = pd.concat([dfctmaxeffco, dfct.sort_values(by='Efficiency',ascending=False).head(1)], ignore_index=True)
    
dfctmaxeffco = dfctmaxeffco.drop(0)
dfctmaxeffco[['City','State','Company','Industry','Zip Code','Efficiency']].sort_values(by='Efficiency', ascending=False).reset_index(drop=True)
Out[191]:
City State Company Industry Zip Code Efficiency
0 New York New York StoneX Diversified Financials 10169 22,200,000
1 El Segundo California A-Mark Precious Metals Wholesalers: Diversified 90245 19,400,000
2 Washington District of Columbia Fannie Mae Diversified Financials 20005 18,621,951
3 McLean Virginia Freddie Mac Diversified Financials 22102 15,074,074
4 San Antonio Texas Valero Energy Petroleum Refining 78249 12,525,253
5 Houston Texas Plains GP Pipelines 77002 11,928,571
6 Toledo Ohio Welltower Real Estate 43615 11,428,571
7 Miami Florida World Kinect Energy 33178 8,978,723
8 Parsippany New Jersey PBF Energy Petroleum Refining 07054 8,487,179
9 Findlay Ohio Marathon Petroleum Petroleum Refining 45840 7,672,131
10 Oklahoma City Oklahoma Devon Energy Mining, Crude-Oil Production 73102 6,913,043
11 Conshohocken Pennsylvania Cencora Wholesalers: Health Care 19428 6,681,818
12 Irving Texas McKesson Wholesalers: Health Care 75039 6,437,500
13 Brentwood Tennessee Delek US Petroleum Refining 37027 6,250,000
14 Denver Colorado Ovintiv Mining, Crude-Oil Production 80202 5,750,000
15 Spring Texas Exxon Mobil Petroleum Refining 77389 5,740,558
16 Midland Texas Diamondback Energy Mining, Crude-Oil Production 79701 5,550,000
17 Dallas Texas HF Sinclair Petroleum Refining 75219 5,396,226
18 Chesterfield Missouri Reinsurance of America Insurance: Life, Health (Stock) 63017 5,390,244
19 Cincinnati Ohio Western & Southern Financial Insurance: Life, Health (Mutual) 45202 5,111,111
20 Milwaukee Wisconsin Northwestern Mutual Insurance: Life, Health (Mutual) 53202 5,048,780
21 Maumee Ohio Andersons Food Production 43537 4,913,043
22 Dublin Ohio Cardinal Health Wholesalers: Health Care 43017 4,685,950
23 Waltham Massachusetts Global Partners Energy 02453 4,526,316
24 Tulsa Oklahoma Oneok Pipelines 74103 4,173,077
25 Springfield Massachusetts Mass Mutual Insurance: Life, Health (Mutual) 01111 3,848,214
26 Newport Beach California Pacific Life Insurance: Life, Health (Stock) 92660 3,674,419
27 Inver Grove Heights Minnesota CHS Food Production 55077 3,672,897
28 Santa Clara California Nvidia Semiconductors and Other Electronic Components 95051 3,625,000
29 Bloomfield Connecticut Cigna Health Care: Pharmacy and Other Services 06002 3,412,983
30 Richmond Virginia Altria Tobacco 23230 3,290,323
31 Greenwich Connecticut Interactive Brokers Securities 06830 3,133,333
32 San Francisco California Prologis Real Estate 94111 3,037,037
33 Los Gatos California Netflix Entertainment 95032 2,785,714
34 Scottsdale Arizona Taylor Morrison Home Homebuilders 85251 2,733,333
35 Minneapolis Minnesota Thrivent Financial for Lutherans Insurance: Life, Health (Mutual) 55415 2,725,000
36 St. Louis Missouri Centene Health Care: Insurance and Managed Care 63105 2,695,868
37 Atlanta Georgia Pulte Homebuilders 30326 2,632,353
38 San Jose California Super Micro Computer Computers, Office Equipment 95131 2,631,579
39 Columbus Ohio Nationwide Insurance: Property and Casualty (Mutual) 43215 2,604,444
40 Arlington Texas D.R. Horton Homebuilders 76011 2,486,486
41 Cupertino California Apple Computers, Office Equipment 95014 2,384,146
42 Boston Massachusetts American Tower Real Estate 02116 2,340,426
43 Fremont California TD Synnex Wholesalers: Electronics and Office Equipment 94538 2,267,442
44 Long Beach California Molina Healthcare Health Care: Insurance and Managed Care 90802 2,255,556
45 Omaha Nebraska Mutual of Omaha Insurance Insurance: Life, Health (Mutual) 68175 2,246,154
46 Menlo Park California Meta Internet Services and Retailing 94025 2,219,973
47 Fort Washington Pennsylvania Toll Brothers Homebuilders 19034 2,204,082
48 Lansing Michigan Auto-Owners Insurance Insurance: Property and Casualty (Mutual) 48917 2,164,384
49 Oakland California Block Financial Data Services 94612 2,114,035
50 Fairfield Ohio Cincinnati Financial Insurance: Property and Casualty (Stock) 45014 2,017,857
51 Chicago Illinois Archer Daniels Midland Food Production 60601 1,979,167
52 Erie Pennsylvania Erie Insurance Insurance: Property and Casualty (Mutual) 16530 1,970,149
53 Madison Wisconsin American Family Insurance Insurance: Property and Casualty (Stock) 53783 1,918,919
54 Mountain View California Alphabet Internet Services and Retailing 94043 1,909,438
55 Radnor Pennsylvania Lincoln National Insurance: Life, Health (Stock) 19087 1,877,551
56 Newark New Jersey Prudential Financial Insurance: Life, Health (Stock) 07102 1,857,520
57 Jacksonville Florida GuideWell Mutual Insurance: Life, Health (Stock) 32246 1,843,575
58 Irvine California Ingram Micro Wholesalers: Electronics and Office Equipment 92612 1,839,080
59 Bloomington Illinois State Farm Insurance: Property and Casualty (Mutual) 61710 1,824,926
60 Arden Hills Minnesota Land O'Lakes Food Consumer Products 55126 1,800,000
61 Johnston Rhode Island FM Insurance: Property and Casualty (Stock) 02919 1,793,103
62 Louisville Kentucky Humana Health Care: Insurance and Managed Care 40202 1,792,998
63 Indianapolis Indiana Elevance Health Health Care: Insurance and Managed Care 46204 1,706,847
64 Baltimore Maryland Constellation Energy Energy 21231 1,661,972
65 Foster City California Gilead Sciences Pharmaceuticals 94404 1,636,364
66 Woodland Hills California Farmers Insurance Exchange Insurance: Property and Casualty (Mutual) 91367 1,565,657
67 El Dorado Arkansas Murphy USA Specialty Retailers: Other 71730 1,543,103
68 Phoenix Arizona Avnet Wholesalers: Electronics and Office Equipment 85034 1,535,484
69 Detroit Michigan Ally Financial Diversified Financials 48226 1,532,710
70 Reston Virginia NVR Homebuilders 20190 1,528,571
71 Columbus Georgia Aflac Insurance: Life, Health (Stock) 31999 1,488,189
72 Juno Beach Florida NextEra Energy Utilities: Gas and Electric 33408 1,476,190
73 St. Paul Minnesota Securian Financial Insurance: Life, Health (Stock) 55101 1,464,286
74 Woonsocket Rhode Island CVS Health Health Care: Pharmacy and Other Services 02895 1,436,609
75 Princeton New Jersey Bristol-Myers Squibb Pharmaceuticals 08543 1,416,422
76 Palo Alto California Broadcom Semiconductors and Other Electronic Components 94304 1,416,216
77 Vernon Hills Illinois CDW Information Technology Services 60061 1,390,728
78 Hartford Connecticut Hartford Insurance Insurance: Property and Casualty (Stock) 06155 1,387,435
79 San Diego California LPL Financial s Securities 92121 1,377,778
80 Arlington Virginia AES Utilities: Gas and Electric 22203 1,351,648
81 Fort Wayne Indiana Steel Dynamics Metals 46804 1,346,154
82 Charlotte North Carolina Sonic Automotive Automotive Retailing, Services 28211 1,314,815
83 Centennial Colorado Arrow Electronics Wholesalers: Electronics and Office Equipment 80112 1,297,674
84 Eden Prairie Minnesota C.H. Robinson Worldwide Transportation and Logistics 55347 1,282,609
85 Cambridge Massachusetts Biogen Pharmaceuticals 02142 1,276,316
86 Allentown Pennsylvania PPL Utilities: Gas and Electric 18101 1,268,657
87 Rosemont Illinois US Foods Wholesalers: Food and Grocery 60018 1,263,333
88 Rosemead California Edison International Utilities: Gas and Electric 91770 1,257,143
89 Corona California Monster Beverage Beverages 92879 1,250,000
90 Medford Oregon Lithia Motors Automotive Retailing, Services 97501 1,211,921
91 Stamford Connecticut Synchrony Financial Diversified Financials 06902 1,210,000
92 Herndon Virginia QXO Building Products Wholesalers: Diversified 20170 1,209,877
93 Midland Michigan Dow Chemicals 48674 1,194,444
94 Thousand Oaks California Amgen Pharmaceuticals 91320 1,192,857
95 Chattanooga Tennessee Unum Insurance: Life, Health (Stock) 37402 1,183,486
96 Northbrook Illinois Allstate Insurance: Property and Casualty (Stock) 60062 1,161,232
97 Englewood Colorado EchoStar Telecommunications 80112 1,153,285
98 Duluth Georgia Asbury Automotive Automotive Retailing, Services 30097 1,146,667
99 Mayfield Village Ohio Progressive Insurance: Property and Casualty (Stock) 44143 1,137,255
100 Riverwoods Illinois Discover Financial Diversified Financials 60015 1,123,810
101 Bellevue Washington Paccar Motor Vehicles & Parts 98004 1,119,601
102 Providence Rhode Island United Natural Foods Wholesalers: Food and Grocery 02908 1,095,406
103 Pittsburgh Pennsylvania WESCO International Wholesalers: Diversified 15219 1,090,000
104 Dearborn Michigan Ford Motor Motor Vehicles & Parts 48126 1,081,871
105 Victor New York Constellation Brands Beverages 14564 1,075,269
106 Redmond Washington Microsoft Computer Software 98052 1,075,000
107 Fort Lauderdale Florida AutoNation Automotive Retailing, Services 33301 1,067,729
108 Akron Ohio FirstEnergy Utilities: Gas and Electric 44308 1,056,911
109 Bloomfield Hills Michigan Penske Automotive Automotive Retailing, Services 48302 1,055,363
110 North Chicago Illinois AbbVie Pharmaceuticals 60064 1,023,636
111 New Braunfels Texas Rush Enterprises Automotive Retailing, Services 78130 987,342
112 Norwalk Connecticut Booking s Internet Services and Retailing 06854 979,339
113 New Orleans Louisiana Entergy Utilities: Gas and Electric 70113 967,480
114 Beverly Hills California Live Nation Entertainment Entertainment 90210 958,678
115 Tarrytown New York Regeneron Pharmaceuticals Pharmaceuticals 10591 940,397
116 Moline Illinois Deere Construction and Farm Machinery 61265 931,532
117 Orrville Ohio J.M. Smucker Food Consumer Products 44667 911,111
118 Jackson Michigan CMS Energy Utilities: Gas and Electric 49201 903,614
119 Round Rock Texas Dell Technologies Computers, Office Equipment 78682 885,185
120 Rahway New Jersey Merck Pharmaceuticals 07065 867,568
121 Raleigh North Carolina First Citizens BancShares Commercial Banks 27609 867,052
122 Newport News Virginia Ferguson Wholesalers: Diversified 23606 845,714
123 San Mateo California Franklin Resources Securities 94403 833,333
124 Seattle Washington Expedia Internet Services and Retailing 98119 830,303
125 Long Island City New York Altice USA Telecommunications 11101 825,688
126 Des Moines Iowa Principal Financial Insurance: Life, Health (Stock) 50392 817,259
127 Westlake Texas Charles Schwab Securities 76262 809,969
128 Tampa Florida Mosaic Chemicals 33602 804,348
129 Purchase New York Mastercard Financial Data Services 10577 798,867
130 Tempe Arizona Carvana Automotive Retailing, Services 85281 787,356
131 St. Petersburg Florida Raymond James Financial Securities 33716 784,211
132 Austin Texas Tesla Motor Vehicles & Parts 78725 777,247
133 Issaquah Washington Costco General Merchandisers 98027 764,264
134 Oak Brook Illinois Ace Hardware Wholesalers: Diversified 60523 760,000
135 Westminster Colorado Ball Packaging, Containers 80021 756,250
136 Glen Allen Virginia Markel Insurance: Property and Casualty (Stock) 23060 754,545
137 Evendale Ohio General Electric Aerospace & Defense 45215 730,189
138 Summit New Jersey Kenvue Household and Personal Products 07901 704,545
139 Lake Forest Illinois W.W. Grainger Wholesalers: Diversified 60045 688,000
140 Philadelphia Pennsylvania Comcast Telecommunications 19103 679,670
141 Kingsport Tennessee Eastman Chemical Chemicals 37660 671,429
142 Camden New Jersey Campbell's Food Consumer Products 08103 666,667
143 Sunny Isles Beach Florida Icahn Enterprises Diversified Financials 33160 666,667
144 Plantation Florida Chewy Internet Services and Retailing 33322 661,111
145 Westchester Illinois Ingredion Food Production 60154 660,714
146 Merriam Kansas Seaboard Food Production 66202 650,000
147 Milpitas California KLA Semiconductors and Other Electronic Components 95035 649,007
148 Beaverton Oregon Nike Apparel 97005 647,355
149 New Brunswick New Jersey Johnson & Johnson Pharmaceuticals 08933 643,012
150 Cleveland Ohio Cleveland-Cliffs Metals 44114 640,000
151 Redwood City California Equinix Real Estate 94065 639,706
152 Byron Center Michigan SpartanNash Wholesalers: Food and Grocery 49315 633,333
153 Marlborough Massachusetts BJ's Wholesale Club General Merchandisers 01752 621,212
154 Birmingham Alabama Vulcan Materials Building Materials, Glass 35242 616,667
155 Buffalo New York M&T Bank Commercial Banks 14203 610,860
156 Chandler Arizona Insight Enterprises Information Technology Services 85286 608,392
157 Manhattan Beach California Skechers U.S.A. Apparel 90266 596,026
158 Austin Minnesota Hormel Foods Food Consumer Products 55912 595,000
159 Bethesda Maryland Lockheed Martin Aerospace & Defense 20817 586,777
160 Deerfield Illinois Walgreens Food & Drug Stores 60015 584,950
161 Hershey Pennsylvania Hershey Food Consumer Products 17033 580,311
162 Oshkosh Wisconsin Oshkosh Construction and Farm Machinery 54902 578,378
163 Sunnyvale California Intuitive Surgical Medical Products and Equipment 94086 538,462
164 Monroe Louisiana Lumen Technologies Telecommunications 71203 524,000
165 Burlington Massachusetts Keurig Dr Pepper Beverages 01803 523,810
166 Boise Idaho Micron Technology Semiconductors and Other Electronic Components 83716 522,917
167 Palm Beach Gardens Florida Carrier Global Industrial Machinery 33418 516,667
168 Wilmington Delaware DuPont Chemicals 19805 516,667
169 Melville New York Henry Schein Wholesalers: Health Care 11747 508,000
170 Memphis Tennessee International Paper Packaging, Containers 38197 502,703
171 Columbus Indiana Cummins Industrial Machinery 47201 489,943
172 Richfield Minnesota Best Buy Specialty Retailers: Other 55423 488,235
173 Canonsburg Pennsylvania Viatris Pharmaceuticals 15317 459,375
174 Melbourne Florida L3Harris Technologies Aerospace & Defense 32919 453,191
175 Warsaw Indiana Zimmer Biomet s Medical Products and Equipment 46580 452,941
176 Ankeny Iowa Casey's General Stores Specialty Retailers: Other 50021 450,151
177 Elkhart Indiana THOR Industries Motor Vehicles & Parts 46514 448,430
178 Burbank California Walt Disney Entertainment 91521 445,854
179 Livonia Michigan Masco Home Equipment, Furnishings 48152 433,333
180 Portage Michigan Stryker Medical Products and Equipment 49002 426,415
181 Falls Church Virginia Northrop Grumman Aerospace & Defense 22042 422,680
182 Pleasanton California Workday Computer Software 94588 409,756
183 Fort Worth Texas American Airlines Airlines 76155 406,602
184 Wilmington Massachusetts Analog Devices Semiconductors and Other Electronic Components 01887 391,667
185 Mooresville North Carolina Lowe's Specialty Retailers: Other 28117 388,399
186 Springdale Arkansas Tyson Foods Food Production 72762 386,232
187 Coral Gables Florida MasTec Engineering & Construction 33134 384,375
188 Maplewood Minnesota Solventum Medical Products and Equipment 55144 377,273
189 Benton Harbor Michigan Whirlpool Electronics, Electrical Equip. 49022 377,273
190 Abbott Park Illinois Abbott Laboratories Medical Products and Equipment 60064 368,421
191 Auburn Hills Michigan BorgWarner Motor Vehicles & Parts 48326 368,146
192 Glenview Illinois Illinois Tool Works Industrial Machinery 60025 361,364
193 Lowell Arkansas J.B. Hunt Transport Services Trucking, Truck Leasing 72745 360,119
194 Coraopolis Pennsylvania Dick's Sporting Goods Specialty Retailers: Other 15108 358,289
195 Winona Minnesota Fastenal Wholesalers: Diversified 55987 357,143
196 Downers Grove Illinois Dover Industrial Machinery 60515 350,000
197 Estero Florida Hertz Automotive Retailing, Services 33928 346,154
198 Bentonville Arkansas Walmart General Merchandisers 72712 324,286
199 New Britain Connecticut Stanley Black & Decker Industrial Machinery 06053 317,526
200 Antioch Tennessee LKQ Wholesalers: Diversified 37013 306,383
201 Roseland New Jersey Automatic Data Processing Diversified Outsourcing Services 07068 300,000
202 Des Peres Missouri Edward Jones Securities 63131 296,364
203 Evansville Indiana Berry Global Packaging, Containers 47710 292,857
204 Bolingbrook Illinois Ulta Beauty Specialty Retailers: Other 60440 289,744
205 Las Vegas Nevada Las Vegas Sands Hotels, Casinos, Resorts 89113 281,796
206 Franklin Lakes New Jersey Becton Dickinson Medical Products and Equipment 07417 272,973
207 Sumner Washington Lululemon athletica Specialty Retailers: Apparel 98390 271,795
208 Menomonee Falls Wisconsin Kohl's General Merchandisers 53051 270,000
209 Nashville Tennessee HCA Healthcare Health Care: Medical Facilities 37203 260,517
210 Westerville Ohio Vertiv s Electronics, Electrical Equip. 43082 258,065
211 Calhoun Georgia Mohawk Industries Home Equipment, Furnishings 30701 257,757
212 Mentor Ohio Avery Dennison Packaging, Containers 44060 251,429
213 Franklin Tennessee Community Health Systems Health Care: Medical Facilities 37067 240,000
214 Lakeland Florida Publix Super Markets Food & Drug Stores 33811 236,078
215 Corning New York Corning Electronics, Electrical Equip. 14831 232,682
216 Reno Nevada Caesars Entertainment Hotels, Casinos, Resorts 89501 226,000
217 Burlington New Jersey Burlington Stores Specialty Retailers: Apparel 08016 224,101
218 Armonk New York IBM Information Technology Services 10504 220,738
219 Chesapeake Virginia Dollar Tree Specialty Retailers: Other 23320 220,630
220 Goodlettsville Tennessee Dollar General Specialty Retailers: Other 37072 209,063
221 Rolling Meadows Illinois Arthur J. Gallagher Diversified Financials 60008 207,143
222 Burlington North Carolina Labcorp s Health Care: Pharmacy and Other Services 27215 198,777
223 Farmington Connecticut Otis Worldwide Industrial Machinery 06032 198,611
224 Dublin California Ross Stores Specialty Retailers: Apparel 94568 197,196
225 Secaucus New Jersey Quest Diagnostics Health Care: Pharmacy and Other Services 07094 196,040
226 Springfield Missouri O'Reilly Automotive Specialty Retailers: Other 65802 195,093
227 King of Prussia Pennsylvania Universal Health Services Health Care: Medical Facilities 19406 180,571
228 Durham North Carolina IQVIA s Health Care: Pharmacy and Other Services 27703 175,000
229 Framingham Massachusetts TJX Specialty Retailers: Apparel 01701 154,945
230 Southfield Michigan Lear Motor Vehicles & Parts 48033 134,139
231 Wallingford Connecticut Amphenol Network and Other Communications Equipment 06492 121,600
232 Ashburn Virginia DXC Technology Information Technology Services 20147 105,385
233 Orlando Florida Darden Restaurants Food Services 32837 59,655
234 Teaneck New Jersey Cognizant Technology Information Technology Services 07666 58,492
235 Plano Texas Yum China s Food Services 75074 46,029
236 Newark California Concentrix Information Technology Services 94560 21,333
In [192]:
# Join the Dataframe 'gdfusact' with 'dfctmaxeffco' for the Top 10
gdfusactmaxeffco = gdfusact.merge(dfctmaxeffco, how = 'inner', on = ['Zip Code'])
gdfusactmaxeffco = gdfusactmaxeffco.sort_values('Efficiency', ascending=False).reset_index(drop=True)
In [193]:
mctmaxeffco = gdfusactmaxeffco.explore(column='Efficiency', name='The Most Efficient Company in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctmaxeffco)
mctmaxeffco
Out[193]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [194]:
# Check the Least Efficient Company in each City
dfctmineffco = df.head(1)
dfctmineffco.insert(0, 'Efficiency', 1) # Add new Column 'Efficiency' to new

for ct in ctslist[0:]:
    dfct = df.where(df['City'] == ct[0]).where(df['State'] == ct[1]).dropna()
    dfct['Efficiency'] = dfct['Revenue (rounded)']/dfct['Employees']
    dfctmineffco = pd.concat([dfctmineffco, dfct.sort_values(by='Efficiency',ascending=True).head(1)], ignore_index=True)
    
dfctmineffco = dfctmineffco.drop(0)
dfctmineffco[['City','State','Company','Industry','Zip Code','Efficiency']].sort_values(by='Efficiency', ascending=False).reset_index(drop=True)
Out[194]:
City State Company Industry Zip Code Efficiency
0 El Segundo California A-Mark Precious Metals Wholesalers: Diversified 90245 19,400,000
1 Findlay Ohio Marathon Petroleum Petroleum Refining 45840 7,672,131
2 Oklahoma City Oklahoma Devon Energy Mining, Crude-Oil Production 73102 6,913,043
3 Conshohocken Pennsylvania Cencora Wholesalers: Health Care 19428 6,681,818
4 Midland Texas Diamondback Energy Mining, Crude-Oil Production 79701 5,550,000
5 Chesterfield Missouri Reinsurance of America Insurance: Life, Health (Stock) 63017 5,390,244
6 Dublin Ohio Cardinal Health Wholesalers: Health Care 43017 4,685,950
7 Inver Grove Heights Minnesota CHS Food Production 55077 3,672,897
8 Bloomfield Connecticut Cigna Health Care: Pharmacy and Other Services 06002 3,412,983
9 Los Gatos California Netflix Entertainment 95032 2,785,714
10 Arlington Texas D.R. Horton Homebuilders 76011 2,486,486
11 Cupertino California Apple Computers, Office Equipment 95014 2,384,146
12 Long Beach California Molina Healthcare Health Care: Insurance and Managed Care 90802 2,255,556
13 Menlo Park California Meta Internet Services and Retailing 94025 2,219,973
14 Fort Washington Pennsylvania Toll Brothers Homebuilders 19034 2,204,082
15 Lansing Michigan Auto-Owners Insurance Insurance: Property and Casualty (Mutual) 48917 2,164,384
16 Fairfield Ohio Cincinnati Financial Insurance: Property and Casualty (Stock) 45014 2,017,857
17 Erie Pennsylvania Erie Insurance Insurance: Property and Casualty (Mutual) 16530 1,970,149
18 Madison Wisconsin American Family Insurance Insurance: Property and Casualty (Stock) 53783 1,918,919
19 Radnor Pennsylvania Lincoln National Insurance: Life, Health (Stock) 19087 1,877,551
20 Irvine California Ingram Micro Wholesalers: Electronics and Office Equipment 92612 1,839,080
21 Bloomington Illinois State Farm Insurance: Property and Casualty (Mutual) 61710 1,824,926
22 Tulsa Oklahoma Williams Pipelines 74172 1,810,345
23 Arden Hills Minnesota Land O'Lakes Food Consumer Products 55126 1,800,000
24 Johnston Rhode Island FM Insurance: Property and Casualty (Stock) 02919 1,793,103
25 Baltimore Maryland Constellation Energy Energy 21231 1,661,972
26 Foster City California Gilead Sciences Pharmaceuticals 94404 1,636,364
27 Woodland Hills California Farmers Insurance Exchange Insurance: Property and Casualty (Mutual) 91367 1,565,657
28 El Dorado Arkansas Murphy USA Specialty Retailers: Other 71730 1,543,103
29 Columbus Georgia Aflac Insurance: Life, Health (Stock) 31999 1,488,189
30 Juno Beach Florida NextEra Energy Utilities: Gas and Electric 33408 1,476,190
31 Woonsocket Rhode Island CVS Health Health Care: Pharmacy and Other Services 02895 1,436,609
32 Princeton New Jersey Bristol-Myers Squibb Pharmaceuticals 08543 1,416,422
33 Vernon Hills Illinois CDW Information Technology Services 60061 1,390,728
34 Hartford Connecticut Hartford Insurance Insurance: Property and Casualty (Stock) 06155 1,387,435
35 Fort Wayne Indiana Steel Dynamics Metals 46804 1,346,154
36 Centennial Colorado Arrow Electronics Wholesalers: Electronics and Office Equipment 80112 1,297,674
37 San Antonio Texas USAA Insurance: Property and Casualty (Stock) 78288 1,278,947
38 Rosemont Illinois US Foods Wholesalers: Food and Grocery 60018 1,263,333
39 Rosemead California Edison International Utilities: Gas and Electric 91770 1,257,143
40 Corona California Monster Beverage Beverages 92879 1,250,000
41 Medford Oregon Lithia Motors Automotive Retailing, Services 97501 1,211,921
42 Herndon Virginia QXO Building Products Wholesalers: Diversified 20170 1,209,877
43 Midland Michigan Dow Chemicals 48674 1,194,444
44 Thousand Oaks California Amgen Pharmaceuticals 91320 1,192,857
45 Chattanooga Tennessee Unum Insurance: Life, Health (Stock) 37402 1,183,486
46 Northbrook Illinois Allstate Insurance: Property and Casualty (Stock) 60062 1,161,232
47 Detroit Michigan General Motors Motor Vehicles & Parts 48265 1,156,790
48 Mayfield Village Ohio Progressive Insurance: Property and Casualty (Stock) 44143 1,137,255
49 Riverwoods Illinois Discover Financial Diversified Financials 60015 1,123,810
50 Springfield Massachusetts Eversource Energy Utilities: Gas and Electric 01104 1,112,150
51 Dearborn Michigan Ford Motor Motor Vehicles & Parts 48126 1,081,871
52 Victor New York Constellation Brands Beverages 14564 1,075,269
53 Redmond Washington Microsoft Computer Software 98052 1,075,000
54 Fort Lauderdale Florida AutoNation Automotive Retailing, Services 33301 1,067,729
55 Bloomfield Hills Michigan Penske Automotive Automotive Retailing, Services 48302 1,055,363
56 Miami Florida Watsco Wholesalers: Diversified 33133 1,041,096
57 North Chicago Illinois AbbVie Pharmaceuticals 60064 1,023,636
58 Eden Prairie Minnesota UnitedHealth Health Care: Insurance and Managed Care 55344 1,000,750
59 New Braunfels Texas Rush Enterprises Automotive Retailing, Services 78130 987,342
60 New Orleans Louisiana Entergy Utilities: Gas and Electric 70113 967,480
61 Tarrytown New York Regeneron Pharmaceuticals Pharmaceuticals 10591 940,397
62 Moline Illinois Deere Construction and Farm Machinery 61265 931,532
63 Palo Alto California HP Computers, Office Equipment 94304 924,138
64 Orrville Ohio J.M. Smucker Food Consumer Products 44667 911,111
65 Jackson Michigan CMS Energy Utilities: Gas and Electric 49201 903,614
66 Round Rock Texas Dell Technologies Computers, Office Equipment 78682 885,185
67 Rahway New Jersey Merck Pharmaceuticals 07065 867,568
68 Scottsdale Arizona Reliance Metals 85254 862,500
69 Oakland California PG&E Utilities: Gas and Electric 94612 859,155
70 Fremont California Lam Research Semiconductors and Other Electronic Components 94538 856,322
71 San Mateo California Franklin Resources Securities 94403 833,333
72 Des Moines Iowa Principal Financial Insurance: Life, Health (Stock) 50392 817,259
73 Westlake Texas Charles Schwab Securities 76262 809,969
74 Newark New Jersey Public Service Enterprise Utilities: Gas and Electric 07102 792,308
75 Tempe Arizona Carvana Automotive Retailing, Services 85281 787,356
76 San Diego California Sempra Utilities: Gas and Electric 92101 785,714
77 Indianapolis Indiana Corteva Food Production 46268 768,182
78 Issaquah Washington Costco General Merchandisers 98027 764,264
79 Oak Brook Illinois Ace Hardware Wholesalers: Diversified 60523 760,000
80 Westminster Colorado Ball Packaging, Containers 80021 756,250
81 Beverly Hills California Endeavor Entertainment 90210 750,000
82 Evendale Ohio General Electric Aerospace & Defense 45215 730,189
83 Summit New Jersey Kenvue Household and Personal Products 07901 704,545
84 Mountain View California Intuit Computer Software 94043 673,554
85 Kingsport Tennessee Eastman Chemical Chemicals 37660 671,429
86 Sunny Isles Beach Florida Icahn Enterprises Diversified Financials 33160 666,667
87 Camden New Jersey Campbell's Food Consumer Products 08103 666,667
88 Plantation Florida Chewy Internet Services and Retailing 33322 661,111
89 Westchester Illinois Ingredion Food Production 60154 660,714
90 Merriam Kansas Seaboard Food Production 66202 650,000
91 Milpitas California KLA Semiconductors and Other Electronic Components 95035 649,007
92 Beaverton Oregon Nike Apparel 97005 647,355
93 Richmond Virginia ARKO Specialty Retailers: Other 23227 644,068
94 New Brunswick New Jersey Johnson & Johnson Pharmaceuticals 08933 643,012
95 Byron Center Michigan SpartanNash Wholesalers: Food and Grocery 49315 633,333
96 Buffalo New York M&T Bank Commercial Banks 14203 610,860
97 Columbus Ohio Huntington Bancshares Commercial Banks 43287 603,015
98 Manhattan Beach California Skechers U.S.A. Apparel 90266 596,026
99 Austin Minnesota Hormel Foods Food Consumer Products 55912 595,000
100 Hershey Pennsylvania Hershey Food Consumer Products 17033 580,311
101 Oshkosh Wisconsin Oshkosh Construction and Farm Machinery 54902 578,378
102 Parsippany New Jersey Avis Budget Automotive Retailing, Services 07054 575,610
103 Bellevue Washington Expeditors International of Washington Transportation and Logistics 98006 560,847
104 Redwood City California Electronic Arts Entertainment 94065 554,745
105 Lake Forest Illinois Packaging Corp. of America Packaging, Containers 60045 545,455
106 Allentown Pennsylvania Air Products & Chemicals Chemicals 18106 540,179
107 Sunnyvale California Intuitive Surgical Medical Products and Equipment 94086 538,462
108 Irving Texas Kimberly-Clark Household and Personal Products 75038 528,947
109 Omaha Nebraska Peter Kiewit Sons' Engineering & Construction 68102 528,302
110 Englewood Colorado QVC Internet Services and Retailing 80112 526,316
111 Monroe Louisiana Lumen Technologies Telecommunications 71203 524,000
112 Burlington Massachusetts Keurig Dr Pepper Beverages 01803 523,810
113 Palm Beach Gardens Florida Carrier Global Industrial Machinery 33418 516,667
114 Wilmington Delaware DuPont Chemicals 19805 516,667
115 Tampa Florida Crown s Packaging, Containers 33637 513,043
116 Melville New York Henry Schein Wholesalers: Health Care 11747 508,000
117 Spring Texas Hewlett Packard Computers, Office Equipment 77389 493,443
118 Columbus Indiana Cummins Industrial Machinery 47201 489,943
119 Richfield Minnesota Best Buy Specialty Retailers: Other 55423 488,235
120 Duluth Georgia AGCO Construction and Farm Machinery 30096 487,500
121 Birmingham Alabama Regions Financial Commercial Banks 35203 479,592
122 Long Island City New York JetBlue Airways Airlines 11101 469,697
123 Glen Allen Virginia Owens & Minor Wholesalers: Health Care 23060 461,207
124 Canonsburg Pennsylvania Viatris Pharmaceuticals 15317 459,375
125 Stamford Connecticut Philip Morris Tobacco 06901 456,077
126 Cambridge Massachusetts GE Vernova Energy 02141 454,427
127 Melbourne Florida L3Harris Technologies Aerospace & Defense 32919 453,191
128 Warsaw Indiana Zimmer Biomet s Medical Products and Equipment 46580 452,941
129 Ankeny Iowa Casey's General Stores Specialty Retailers: Other 50021 450,151
130 Elkhart Indiana THOR Industries Motor Vehicles & Parts 46514 448,430
131 Burbank California Walt Disney Entertainment 91521 445,854
132 Toledo Ohio Owens Corning Building Materials, Glass 43659 440,000
133 Livonia Michigan Masco Home Equipment, Furnishings 48152 433,333
134 Portage Michigan Stryker Medical Products and Equipment 49002 426,415
135 Falls Church Virginia Northrop Grumman Aerospace & Defense 22042 422,680
136 Boston Massachusetts State Street Commercial Banks 02114 420,152
137 Santa Clara California ServiceNow Computer Software 95054 418,251
138 Pleasanton California Workday Computer Software 94588 409,756
139 Fort Worth Texas American Airlines Airlines 76155 406,602
140 Providence Rhode Island Textron Aerospace & Defense 02903 402,941
141 Boise Idaho Albertsons Food & Drug Stores 83706 402,848
142 Deerfield Illinois Baxter International Medical Products and Equipment 60015 397,368
143 Wilmington Massachusetts Analog Devices Semiconductors and Other Electronic Components 01887 391,667
144 Mooresville North Carolina Lowe's Specialty Retailers: Other 28117 388,399
145 Arlington Virginia Boeing Aerospace & Defense 22202 386,628
146 Springdale Arkansas Tyson Foods Food Production 72762 386,232
147 Brentwood Tennessee Tractor Supply Specialty Retailers: Other 37027 382,051
148 Charlotte North Carolina Honeywell Industrial Machinery 28202 377,451
149 Benton Harbor Michigan Whirlpool Electronics, Electrical Equip. 49022 377,273
150 Maplewood Minnesota Solventum Medical Products and Equipment 55144 377,273
151 Washington District of Columbia Xylem Industrial Machinery 20003 373,913
152 Abbott Park Illinois Abbott Laboratories Medical Products and Equipment 60064 368,421
153 Norwalk Connecticut EMCOR Engineering & Construction 06851 361,386
154 Glenview Illinois Illinois Tool Works Industrial Machinery 60025 361,364
155 Lowell Arkansas J.B. Hunt Transport Services Trucking, Truck Leasing 72745 360,119
156 Coraopolis Pennsylvania Dick's Sporting Goods Specialty Retailers: Other 15108 358,289
157 Winona Minnesota Fastenal Wholesalers: Diversified 55987 357,143
158 Downers Grove Illinois Dover Industrial Machinery 60515 350,000
159 Estero Florida Hertz Automotive Retailing, Services 33928 346,154
160 Waltham Massachusetts Thermo Fisher Scientific Scientific, Photographic and Control Equipment 02451 343,200
161 Chandler Arizona Microchip Technology Semiconductors and Other Electronic Components 85224 340,807
162 Austin Texas Oracle Computer Software 78741 333,333
163 St. Paul Minnesota Ecolab Chemicals 55102 327,083
164 Cleveland Ohio Parker-Hannifin Industrial Machinery 44124 325,696
165 Bentonville Arkansas Walmart General Merchandisers 72712 324,286
166 New Britain Connecticut Stanley Black & Decker Industrial Machinery 06053 317,526
167 Marlborough Massachusetts Boston Scientific Medical Products and Equipment 01752 315,094
168 Reston Virginia Science Applications International Information Technology Services 20190 312,500
169 Pittsburgh Pennsylvania Howmet Aerospace Aerospace & Defense 15212 309,623
170 Milwaukee Wisconsin Rockwell Automation Electronics, Electrical Equip. 53204 307,407
171 Antioch Tennessee LKQ Wholesalers: Diversified 37013 306,383
172 Roseland New Jersey Automatic Data Processing Diversified Outsourcing Services 07068 300,000
173 Des Peres Missouri Edward Jones Securities 63131 296,364
174 Evansville Indiana Berry Global Packaging, Containers 47710 292,857
175 Bolingbrook Illinois Ulta Beauty Specialty Retailers: Other 60440 289,744
176 Purchase New York PepsiCo Food Consumer Products 10577 288,088
177 Akron Ohio Goodyear Tire & Rubber Motor Vehicles & Parts 44316 277,941
178 Franklin Lakes New Jersey Becton Dickinson Medical Products and Equipment 07417 272,973
179 Sumner Washington Lululemon athletica Specialty Retailers: Apparel 98390 271,795
180 Menomonee Falls Wisconsin Kohl's General Merchandisers 53051 270,000
181 Newport News Virginia Huntington Ingalls Industries Aerospace & Defense 23607 261,364
182 Nashville Tennessee HCA Healthcare Health Care: Medical Facilities 37203 260,517
183 Maumee Ohio Dana Motor Vehicles & Parts 43537 260,101
184 Westerville Ohio Vertiv s Electronics, Electrical Equip. 43082 258,065
185 Calhoun Georgia Mohawk Industries Home Equipment, Furnishings 30701 257,757
186 Mentor Ohio Avery Dennison Packaging, Containers 44060 251,429
187 Las Vegas Nevada MGM Resorts International Hotels, Casinos, Resorts 89109 249,275
188 Coral Gables Florida Ryder System Transportation and Logistics 33134 248,521
189 Atlanta Georgia UPS Mail, Package and Freight Delivery 30328 244,761
190 Minneapolis Minnesota Target General Merchandisers 55403 242,273
191 Dallas Texas Tenet Healthcare Health Care: Medical Facilities 75254 240,139
192 Franklin Tennessee Community Health Systems Health Care: Medical Facilities 37067 240,000
193 St. Louis Missouri Emerson Electric Industrial Machinery 63136 239,726
194 Louisville Kentucky Yum Brands Food Services 40213 236,593
195 Lakeland Florida Publix Super Markets Food & Drug Stores 33811 236,078
196 Corning New York Corning Electronics, Electrical Equip. 14831 232,682
197 Raleigh North Carolina Advance Auto Parts Specialty Retailers: Other 27609 227,083
198 Reno Nevada Caesars Entertainment Hotels, Casinos, Resorts 89501 226,000
199 Burlington New Jersey Burlington Stores Specialty Retailers: Apparel 08016 224,101
200 Armonk New York IBM Information Technology Services 10504 220,738
201 Chesapeake Virginia Dollar Tree Specialty Retailers: Other 23320 220,630
202 San Jose California Sanmina Semiconductors and Other Electronic Components 95134 220,290
203 Phoenix Arizona Sprouts Farmers Market Food & Drug Stores 85054 220,000
204 Jacksonville Florida Fidelity National Information Financial Data Services 32202 210,000
205 St. Petersburg Florida Jabil Semiconductors and Other Electronic Components 33716 209,420
206 Goodlettsville Tennessee Dollar General Specialty Retailers: Other 37072 209,063
207 Rolling Meadows Illinois Arthur J. Gallagher Diversified Financials 60008 207,143
208 Cincinnati Ohio Cintas Diversified Outsourcing Services 45262 206,452
209 Houston Texas KBR Information Technology Services 77002 202,632
210 Burlington North Carolina Labcorp s Health Care: Pharmacy and Other Services 27215 198,777
211 Farmington Connecticut Otis Worldwide Industrial Machinery 06032 198,611
212 Dublin California Ross Stores Specialty Retailers: Apparel 94568 197,196
213 Secaucus New Jersey Quest Diagnostics Health Care: Pharmacy and Other Services 07094 196,040
214 Springfield Missouri O'Reilly Automotive Specialty Retailers: Other 65802 195,093
215 San Francisco California Gap Specialty Retailers: Apparel 94105 184,146
216 Memphis Tennessee AutoZone Specialty Retailers: Other 38103 183,532
217 King of Prussia Pennsylvania Universal Health Services Health Care: Medical Facilities 19406 180,571
218 Durham North Carolina IQVIA s Health Care: Pharmacy and Other Services 27703 175,000
219 Chicago Illinois McDonald's Food Services 60607 172,667
220 Denver Colorado DaVita Health Care: Medical Facilities 80202 168,421
221 Auburn Hills Michigan Autoliv Motor Vehicles & Parts 48326 166,934
222 Bethesda Maryland Marriott International Hotels, Casinos, Resorts 20814 161,935
223 Framingham Massachusetts TJX Specialty Retailers: Apparel 01701 154,945
224 Southfield Michigan Lear Motor Vehicles & Parts 48033 134,139
225 Wallingford Connecticut Amphenol Network and Other Communications Equipment 06492 121,600
226 Ashburn Virginia DXC Technology Information Technology Services 20147 105,385
227 Seattle Washington Starbucks Food Services 98134 100,277
228 Greenwich Connecticut GXO Logistics Transportation and Logistics 06831 91,051
229 Newport Beach California Chipotle Mexican Grill Food Services 92660 86,590
230 New York New York ABM Industries Diversified Outsourcing Services 10006 71,795
231 Philadelphia Pennsylvania Aramark Diversified Outsourcing Services 19103 65,242
232 McLean Virginia Hilton Hotels, Casinos, Resorts 22102 61,878
233 Orlando Florida Darden Restaurants Food Services 32837 59,655
234 Teaneck New Jersey Cognizant Technology Information Technology Services 07666 58,492
235 Plano Texas Yum China s Food Services 75074 46,029
236 Newark California Concentrix Information Technology Services 94560 21,333
In [195]:
# Join the Dataframe 'gdfusact' with 'dfctmineffco' for the Top 10
gdfusactmineffco = gdfusact.merge(dfctmineffco, how = 'inner', on = ['Zip Code'])
gdfusactmineffco = gdfusactmineffco.sort_values('Efficiency', ascending=False).reset_index(drop=True)
In [196]:
mctmineffco = gdfusactmineffco.explore(column='Efficiency', name='The Least Efficient Company in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctmineffco)
mctmineffco
Out[196]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [197]:
# Check the Average Efficiency in each City
dfctavreff = df.head(1)
dfctavreff.insert(0, 'Efficiency', 1) # Add new Column 'Efficiency' to new

for ct in ctslist[0:]:
    dfct = df.where(df['City'] == ct[0]).dropna().where(df['State'] == ct[1]).dropna()
    dfct['Efficiency'] = dfct['Revenue (rounded)']/dfct['Employees']
    #print(dfct.groupby(['State','City'], as_index=False).mean('Efficiency'))
    dfctavreff = pd.concat([dfctavreff, dfct.groupby(['State','City'], as_index=False).mean('Efficiency')], ignore_index=True)[['State','City','Efficiency']]
    
dfctavreff = dfctavreff.drop(0)
dfctavreff.sort_values(by='Efficiency', ascending=False).reset_index(drop=True)
Out[197]:
State City Efficiency
0 California El Segundo 19,400,000
1 Ohio Findlay 7,672,131
2 Oklahoma Oklahoma City 6,913,043
3 Texas San Antonio 6,902,100
4 Pennsylvania Conshohocken 6,681,818
5 District of Columbia Washington 6,460,449
6 Ohio Toledo 5,934,286
7 Texas Midland 5,550,000
8 Missouri Chesterfield 5,390,244
9 Ohio Dublin 4,685,950
10 Florida Miami 4,227,158
11 Virginia McLean 4,118,383
12 Minnesota Inver Grove Heights 3,672,897
13 Texas Houston 3,515,320
14 Connecticut Bloomfield 3,412,983
15 Tennessee Brentwood 3,316,026
16 New Jersey Parsippany 3,245,567
17 Texas Spring 3,117,000
18 Oklahoma Tulsa 2,991,711
19 California Los Gatos 2,785,714
20 Ohio Maumee 2,586,572
21 Texas Arlington 2,486,486
22 Massachusetts Springfield 2,480,182
23 Massachusetts Waltham 2,434,758
24 California Cupertino 2,384,146
25 California Long Beach 2,255,556
26 California Menlo Park 2,219,973
27 Pennsylvania Fort Washington 2,204,082
28 Michigan Lansing 2,164,384
29 Ohio Fairfield 2,017,857
30 New York New York 2,015,087
31 Pennsylvania Erie 1,970,149
32 Wisconsin Madison 1,918,919
33 California Newport Beach 1,880,504
34 Pennsylvania Radnor 1,877,551
35 California Irvine 1,839,080
36 Illinois Bloomington 1,824,926
37 Minnesota Arden Hills 1,800,000
38 Colorado Denver 1,799,566
39 Arizona Scottsdale 1,797,917
40 Rhode Island Johnston 1,793,103
41 Maryland Baltimore 1,661,972
42 California Foster City 1,636,364
43 Texas Irving 1,585,504
44 California Woodland Hills 1,565,657
45 California Fremont 1,561,882
46 Wisconsin Milwaukee 1,558,929
47 Arkansas El Dorado 1,543,103
48 Virginia Richmond 1,492,470
49 Texas Dallas 1,489,891
50 Georgia Columbus 1,488,189
51 California Oakland 1,486,595
52 Florida Juno Beach 1,476,190
53 Ohio Columbus 1,472,016
54 Rhode Island Woonsocket 1,436,609
55 New Jersey Princeton 1,416,422
56 Illinois Vernon Hills 1,390,728
57 Connecticut Hartford 1,387,435
58 Massachusetts Boston 1,361,465
59 Ohio Cincinnati 1,354,012
60 Indiana Fort Wayne 1,346,154
61 Michigan Detroit 1,335,097
62 New Jersey Newark 1,324,914
63 Colorado Centennial 1,297,674
64 California Mountain View 1,291,496
65 Illinois Rosemont 1,263,333
66 California Rosemead 1,257,143
67 Connecticut Greenwich 1,252,711
68 California Corona 1,250,000
69 Missouri St. Louis 1,216,159
70 Oregon Medford 1,211,921
71 Virginia Herndon 1,209,877
72 Michigan Midland 1,194,444
73 California Thousand Oaks 1,192,857
74 Tennessee Chattanooga 1,183,486
75 California Palo Alto 1,170,177
76 Illinois Northbrook 1,161,232
77 Indiana Indianapolis 1,144,158
78 Minnesota Eden Prairie 1,141,679
79 Ohio Mayfield Village 1,137,255
80 Illinois Riverwoods 1,123,810
81 California Santa Clara 1,122,844
82 Nebraska Omaha 1,116,963
83 Minnesota Minneapolis 1,108,596
84 Michigan Dearborn 1,081,871
85 New York Victor 1,075,269
86 Washington Redmond 1,075,000
87 Florida Fort Lauderdale 1,067,729
88 Michigan Bloomfield Hills 1,055,363
89 Illinois North Chicago 1,023,636
90 California San Francisco 1,023,212
91 Texas New Braunfels 987,342
92 California San Diego 986,470
93 Louisiana New Orleans 967,480
94 California San Jose 943,023
95 New York Tarrytown 940,397
96 Illinois Moline 931,532
97 Ohio Orrville 911,111
98 Pennsylvania Allentown 904,418
99 Michigan Jackson 903,614
100 North Carolina Charlotte 891,162
101 Texas Round Rock 885,185
102 New Jersey Rahway 867,568
103 Massachusetts Cambridge 865,371
104 California Beverly Hills 854,339
105 Washington Bellevue 840,224
106 Colorado Englewood 839,800
107 California San Mateo 833,333
108 Iowa Des Moines 817,259
109 Georgia Duluth 817,083
110 Florida Jacksonville 813,394
111 Texas Westlake 809,969
112 Arizona Tempe 787,356
113 Kentucky Louisville 778,332
114 Washington Issaquah 764,264
115 Illinois Oak Brook 760,000
116 Arizona Phoenix 757,793
117 Colorado Westminster 756,250
118 Rhode Island Providence 738,370
119 Minnesota St. Paul 730,456
120 Ohio Evendale 730,189
121 Virginia Arlington 724,049
122 Georgia Atlanta 711,349
123 New Jersey Summit 704,545
124 Connecticut Stamford 699,383
125 Illinois Chicago 677,019
126 Tennessee Kingsport 671,429
127 Connecticut Norwalk 670,362
128 Ohio Akron 667,426
129 New Jersey Camden 666,667
130 Florida Sunny Isles Beach 666,667
131 Florida Plantation 661,111
132 Illinois Westchester 660,714
133 Florida Tampa 658,696
134 Kansas Merriam 650,000
135 California Milpitas 649,007
136 New York Long Island City 647,693
137 Oregon Beaverton 647,355
138 New Jersey New Brunswick 643,012
139 Michigan Byron Center 633,333
140 Pennsylvania Pittsburgh 618,757
141 Illinois Lake Forest 616,727
142 New York Buffalo 610,860
143 Virginia Glen Allen 607,876
144 California Redwood City 597,225
145 California Manhattan Beach 596,026
146 Minnesota Austin 595,000
147 Virginia Reston 583,503
148 Pennsylvania Hershey 580,311
149 Wisconsin Oshkosh 578,378
150 Texas Austin 555,290
151 Virginia Newport News 553,539
152 Alabama Birmingham 548,129
153 North Carolina Raleigh 547,068
154 New York Purchase 543,477
155 California Sunnyvale 538,462
156 Louisiana Monroe 524,000
157 Massachusetts Burlington 523,810
158 Delaware Wilmington 516,667
159 Florida Palm Beach Gardens 516,667
160 New York Melville 508,000
161 Florida St. Petersburg 496,815
162 Illinois Deerfield 491,159
163 Indiana Columbus 489,943
164 Minnesota Richfield 488,235
165 Arizona Chandler 474,599
166 Ohio Cleveland 470,144
167 Massachusetts Marlborough 468,153
168 Idaho Boise 462,883
169 Pennsylvania Canonsburg 459,375
170 Florida Melbourne 453,191
171 Indiana Warsaw 452,941
172 Iowa Ankeny 450,151
173 Indiana Elkhart 448,430
174 California Burbank 445,854
175 Michigan Livonia 433,333
176 Michigan Portage 426,415
177 Virginia Falls Church 422,680
178 California Pleasanton 409,756
179 Texas Fort Worth 406,602
180 Washington Seattle 398,315
181 Massachusetts Wilmington 391,667
182 North Carolina Mooresville 388,399
183 Arkansas Springdale 386,232
184 Minnesota Maplewood 377,273
185 Michigan Benton Harbor 377,273
186 Maryland Bethesda 374,356
187 Pennsylvania Philadelphia 372,456
188 Illinois Abbott Park 368,421
189 Illinois Glenview 361,364
190 Arkansas Lowell 360,119
191 Pennsylvania Coraopolis 358,289
192 Minnesota Winona 357,143
193 Illinois Downers Grove 350,000
194 Florida Estero 346,154
195 Arkansas Bentonville 324,286
196 Connecticut New Britain 317,526
197 Florida Coral Gables 316,448
198 Tennessee Antioch 306,383
199 New Jersey Roseland 300,000
200 Tennessee Memphis 298,002
201 Missouri Des Peres 296,364
202 Indiana Evansville 292,857
203 Illinois Bolingbrook 289,744
204 New Jersey Franklin Lakes 272,973
205 Washington Sumner 271,795
206 Wisconsin Menomonee Falls 270,000
207 Michigan Auburn Hills 267,540
208 Nevada Las Vegas 265,535
209 Tennessee Nashville 260,517
210 Ohio Westerville 258,065
211 Georgia Calhoun 257,757
212 Ohio Mentor 251,429
213 Tennessee Franklin 240,000
214 Florida Lakeland 236,078
215 New York Corning 232,682
216 Nevada Reno 226,000
217 New Jersey Burlington 224,101
218 New York Armonk 220,738
219 Virginia Chesapeake 220,630
220 Tennessee Goodlettsville 209,063
221 Illinois Rolling Meadows 207,143
222 North Carolina Burlington 198,777
223 Connecticut Farmington 198,611
224 California Dublin 197,196
225 New Jersey Secaucus 196,040
226 Missouri Springfield 195,093
227 Pennsylvania King of Prussia 180,571
228 North Carolina Durham 175,000
229 Massachusetts Framingham 154,945
230 Michigan Southfield 134,139
231 Connecticut Wallingford 121,600
232 Virginia Ashburn 105,385
233 Florida Orlando 59,655
234 New Jersey Teaneck 58,492
235 Texas Plano 46,029
236 California Newark 21,333
In [ ]:
 
In [198]:
# Join the Dataframe 'gdfusact' with 'dfctavreff' for the Top 10
dfctavreff = dfctavreff.merge(df[['City','State','Company','Zip Code']], how = 'inner', on = ['City','State']).sort_values('Efficiency', ascending=False).reset_index(drop=True)
dfctavreff
Out[198]:
State City Efficiency Company Zip Code
0 California El Segundo 19,400,000 A-Mark Precious Metals 90245
1 Ohio Findlay 7,672,131 Marathon Petroleum 45840
2 Oklahoma Oklahoma City 6,913,043 Devon Energy 73102
3 Texas San Antonio 6,902,100 USAA 78288
4 Texas San Antonio 6,902,100 Valero Energy 78249
5 Pennsylvania Conshohocken 6,681,818 Cencora 19428
6 District of Columbia Washington 6,460,449 Xylem 20003
7 District of Columbia Washington 6,460,449 Danaher 20037
8 District of Columbia Washington 6,460,449 Fannie Mae 20005
9 Ohio Toledo 5,934,286 Welltower 43615
10 Ohio Toledo 5,934,286 Owens Corning 43659
11 Texas Midland 5,550,000 Diamondback Energy 79701
12 Missouri Chesterfield 5,390,244 Reinsurance of America 63017
13 Ohio Dublin 4,685,950 Cardinal Health 43017
14 Florida Miami 4,227,158 World Kinect 33178
15 Florida Miami 4,227,158 Watsco 33133
16 Florida Miami 4,227,158 Lennar 33126
17 Virginia McLean 4,118,383 Freddie Mac 22102
18 Virginia McLean 4,118,383 Capital One 22102
19 Virginia McLean 4,118,383 Hilton 22102
20 Virginia McLean 4,118,383 Booz Allen Hamilton 22102
21 Minnesota Inver Grove Heights 3,672,897 CHS 55077
22 Texas Houston 3,515,320 Waste Management 77002
23 Texas Houston 3,515,320 Kinder Morgan 77002
24 Texas Houston 3,515,320 Corebridge Financial 77019
25 Texas Houston 3,515,320 Targa Resources 77002
26 Texas Houston 3,515,320 Cheniere Energy 77002
27 Texas Houston 3,515,320 KBR 77002
28 Texas Houston 3,515,320 Westlake 77056
29 Texas Houston 3,515,320 APA 77042
30 Texas Houston 3,515,320 NOV 77042
31 Texas Houston 3,515,320 CenterPoint Energy 77002
32 Texas Houston 3,515,320 Par Pacific 77024
33 Texas Houston 3,515,320 Quanta Services 77008
34 Texas Houston 3,515,320 Halliburton 77032
35 Texas Houston 3,515,320 1 Automotive 77024
36 Texas Houston 3,515,320 EOG Resources 77002
37 Texas Houston 3,515,320 Enterprise Products Partners 77002
38 Texas Houston 3,515,320 Chevron 77002
39 Texas Houston 3,515,320 Phillips 66 77042
40 Texas Houston 3,515,320 Occidental Petroleum 77046
41 Texas Houston 3,515,320 Sysco 77077
42 Texas Houston 3,515,320 Baker Hughes 77079
43 Texas Houston 3,515,320 NRG Energy 77002
44 Texas Houston 3,515,320 Plains GP 77002
45 Texas Houston 3,515,320 ConocoPhillips 77079
46 Connecticut Bloomfield 3,412,983 Cigna 06002
47 Tennessee Brentwood 3,316,026 Tractor Supply 37027
48 Tennessee Brentwood 3,316,026 Delek US 37027
49 New Jersey Parsippany 3,245,567 Avis Budget 07054
50 New Jersey Parsippany 3,245,567 PBF Energy 07054
51 New Jersey Parsippany 3,245,567 Zoetis 07054
52 Texas Spring 3,117,000 Exxon Mobil 77389
53 Texas Spring 3,117,000 Hewlett Packard 77389
54 Oklahoma Tulsa 2,991,711 Williams 74172
55 Oklahoma Tulsa 2,991,711 Oneok 74103
56 California Los Gatos 2,785,714 Netflix 95032
57 Ohio Maumee 2,586,572 Andersons 43537
58 Ohio Maumee 2,586,572 Dana 43537
59 Texas Arlington 2,486,486 D.R. Horton 76011
60 Massachusetts Springfield 2,480,182 Eversource Energy 01104
61 Massachusetts Springfield 2,480,182 Mass Mutual 01111
62 Massachusetts Waltham 2,434,758 Thermo Fisher Scientific 02451
63 Massachusetts Waltham 2,434,758 Global Partners 02453
64 California Cupertino 2,384,146 Apple 95014
65 California Long Beach 2,255,556 Molina Healthcare 90802
66 California Menlo Park 2,219,973 Meta 94025
67 Pennsylvania Fort Washington 2,204,082 Toll Brothers 19034
68 Michigan Lansing 2,164,384 Auto-Owners Insurance 48917
69 Ohio Fairfield 2,017,857 Cincinnati Financial 45014
70 New York New York 2,015,087 Citi 10013
71 New York New York 2,015,087 Verizon 10036
72 New York New York 2,015,087 Goldman Sachs 10282
73 New York New York 2,015,087 Morgan Stanley 10036
74 New York New York 2,015,087 American Express 10285
75 New York New York 2,015,087 StoneX 10169
76 New York New York 2,015,087 JPMorgan Chase 10017
77 New York New York 2,015,087 MetLife 10166
78 New York New York 2,015,087 PVH 10017
79 New York New York 2,015,087 Omnicom 10017
80 New York New York 2,015,087 Estée Lauder 10153
81 New York New York 2,015,087 Interpublic 10022
82 New York New York 2,015,087 Foot Locker 10001
83 New York New York 2,015,087 Consolidated Edison 10003
84 New York New York 2,015,087 S&P Global 10041
85 New York New York 2,015,087 Voya Financial 10169
86 New York New York 2,015,087 ABM Industries 10006
87 New York New York 2,015,087 Sirius XM 10020
88 New York New York 2,015,087 Guardian Life 10001
89 New York New York 2,015,087 Oscar Health 10013
90 New York New York 2,015,087 Pfizer 10001
91 New York New York 2,015,087 News Corp. 10036
92 New York New York 2,015,087 Jefferies Financial 10022
93 New York New York 2,015,087 Fox 10036
94 New York New York 2,015,087 Blackstone 10154
95 New York New York 2,015,087 Hess 10036
96 New York New York 2,015,087 Equitable 10105
97 New York New York 2,015,087 Kyndryl s 10017
98 New York New York 2,015,087 International Flavors & Fragrances 10019
99 New York New York 2,015,087 Loews 10019
100 New York New York 2,015,087 Paramount Global 10036
101 New York New York 2,015,087 Colgate-Palmolive 10022
102 New York New York 2,015,087 BlackRock 10001
103 New York New York 2,015,087 Macy's 10001
104 New York New York 2,015,087 New York Life Insurance 10010
105 New York New York 2,015,087 TIAA 10017
106 New York New York 2,015,087 Travelers 10017
107 New York New York 2,015,087 Marsh & McLennan 10036
108 New York New York 2,015,087 Apollo Global Management 10019
109 New York New York 2,015,087 American International 10020
110 New York New York 2,015,087 Bank of New York 10286
111 New York New York 2,015,087 Warner Bros. Discovery 10003
112 New York New York 2,015,087 KKR 10001
113 Pennsylvania Erie 1,970,149 Erie Insurance 16530
114 Wisconsin Madison 1,918,919 American Family Insurance 53783
115 California Newport Beach 1,880,504 Pacific Life 92660
116 California Newport Beach 1,880,504 Chipotle Mexican Grill 92660
117 Pennsylvania Radnor 1,877,551 Lincoln National 19087
118 California Irvine 1,839,080 Ingram Micro 92612
119 Illinois Bloomington 1,824,926 State Farm 61710
120 Minnesota Arden Hills 1,800,000 Land O'Lakes 55126
121 Colorado Denver 1,799,566 VF 80202
122 Colorado Denver 1,799,566 Ovintiv 80202
123 Colorado Denver 1,799,566 Newmont 80237
124 Colorado Denver 1,799,566 DaVita 80202
125 Arizona Scottsdale 1,797,917 Reliance 85254
126 Arizona Scottsdale 1,797,917 Taylor Morrison Home 85251
127 Rhode Island Johnston 1,793,103 FM 02919
128 Maryland Baltimore 1,661,972 Constellation Energy 21231
129 California Foster City 1,636,364 Gilead Sciences 94404
130 Texas Irving 1,585,504 Commercial Metals 75039
131 Texas Irving 1,585,504 Vistra 75039
132 Texas Irving 1,585,504 McKesson 75039
133 Texas Irving 1,585,504 Builders FirstSource 75039
134 Texas Irving 1,585,504 Kimberly-Clark 75038
135 Texas Irving 1,585,504 Celanese 75039
136 Texas Irving 1,585,504 Fluor 75039
137 Texas Irving 1,585,504 Caterpillar 75039
138 California Woodland Hills 1,565,657 Farmers Insurance Exchange 91367
139 California Fremont 1,561,882 TD Synnex 94538
140 California Fremont 1,561,882 Lam Research 94538
141 Wisconsin Milwaukee 1,558,929 Rockwell Automation 53204
142 Wisconsin Milwaukee 1,558,929 WEC Energy 53203
143 Wisconsin Milwaukee 1,558,929 Manpower 53212
144 Wisconsin Milwaukee 1,558,929 Fiserv 53203
145 Wisconsin Milwaukee 1,558,929 Northwestern Mutual 53202
146 Arkansas El Dorado 1,543,103 Murphy USA 71730
147 Virginia Richmond 1,492,470 ARKO 23227
148 Virginia Richmond 1,492,470 Dominion Energy 23219
149 Virginia Richmond 1,492,470 Altria 23230
150 Virginia Richmond 1,492,470 CarMax 23238
151 Virginia Richmond 1,492,470 Performance Food 23238
152 Texas Dallas 1,489,891 Texas Instruments 75243
153 Texas Dallas 1,489,891 AECOM 75240
154 Texas Dallas 1,489,891 Tenet Healthcare 75254
155 Texas Dallas 1,489,891 AT&T 75202
156 Texas Dallas 1,489,891 Energy Transfer 75225
157 Texas Dallas 1,489,891 CBRE 75201
158 Texas Dallas 1,489,891 HF Sinclair 75219
159 Texas Dallas 1,489,891 Southwest Airlines 75235
160 Texas Dallas 1,489,891 Jacobs Solutions 75201
161 Georgia Columbus 1,488,189 Aflac 31999
162 California Oakland 1,486,595 PG&E 94612
163 California Oakland 1,486,595 Block 94612
164 Florida Juno Beach 1,476,190 NextEra Energy 33408
165 Ohio Columbus 1,472,016 Nationwide 43215
166 Ohio Columbus 1,472,016 American Electric Power 43215
167 Ohio Columbus 1,472,016 Huntington Bancshares 43287
168 Rhode Island Woonsocket 1,436,609 CVS Health 02895
169 New Jersey Princeton 1,416,422 Bristol-Myers Squibb 08543
170 Illinois Vernon Hills 1,390,728 CDW 60061
171 Connecticut Hartford 1,387,435 Hartford Insurance 06155
172 Massachusetts Boston 1,361,465 State Street 02114
173 Massachusetts Boston 1,361,465 Vertex Pharmaceuticals 02210
174 Massachusetts Boston 1,361,465 American Tower 02116
175 Massachusetts Boston 1,361,465 Wayfair 02116
176 Massachusetts Boston 1,361,465 Liberty Mutual Insurance 02116
177 Ohio Cincinnati 1,354,012 Fifth Third Bancorp 45263
178 Ohio Cincinnati 1,354,012 Kroger 45202
179 Ohio Cincinnati 1,354,012 Procter & Gamble 45202
180 Ohio Cincinnati 1,354,012 Western & Southern Financial 45202
181 Ohio Cincinnati 1,354,012 Cintas 45262
182 Ohio Cincinnati 1,354,012 American Financial 45202
183 Indiana Fort Wayne 1,346,154 Steel Dynamics 46804
184 Michigan Detroit 1,335,097 Ally Financial 48226
185 Michigan Detroit 1,335,097 DTE Energy 48226
186 Michigan Detroit 1,335,097 General Motors 48265
187 New Jersey Newark 1,324,914 Prudential Financial 07102
188 New Jersey Newark 1,324,914 Public Service Enterprise 07102
189 Colorado Centennial 1,297,674 Arrow Electronics 80112
190 California Mountain View 1,291,496 Alphabet 94043
191 California Mountain View 1,291,496 Intuit 94043
192 Illinois Rosemont 1,263,333 US Foods 60018
193 California Rosemead 1,257,143 Edison International 91770
194 Connecticut Greenwich 1,252,711 W.R. Berkley 06830
195 Connecticut Greenwich 1,252,711 GXO Logistics 06831
196 Connecticut Greenwich 1,252,711 XPO 06831
197 Connecticut Greenwich 1,252,711 Interactive Brokers 06830
198 California Corona 1,250,000 Monster Beverage 92879
199 Missouri St. Louis 1,216,159 Emerson Electric 63136
200 Missouri St. Louis 1,216,159 Post s 63144
201 Missouri St. Louis 1,216,159 Core & Main 63146
202 Missouri St. Louis 1,216,159 Graybar Electric 63105
203 Missouri St. Louis 1,216,159 Centene 63105
204 Oregon Medford 1,211,921 Lithia Motors 97501
205 Virginia Herndon 1,209,877 QXO Building Products 20170
206 Michigan Midland 1,194,444 Dow 48674
207 California Thousand Oaks 1,192,857 Amgen 91320
208 Tennessee Chattanooga 1,183,486 Unum 37402
209 California Palo Alto 1,170,177 Broadcom 94304
210 California Palo Alto 1,170,177 HP 94304
211 Illinois Northbrook 1,161,232 Allstate 60062
212 Indiana Indianapolis 1,144,158 Corteva 46268
213 Indiana Indianapolis 1,144,158 Elevance Health 46204
214 Indiana Indianapolis 1,144,158 Eli Lilly 46285
215 Minnesota Eden Prairie 1,141,679 UnitedHealth 55344
216 Minnesota Eden Prairie 1,141,679 C.H. Robinson Worldwide 55347
217 Ohio Mayfield Village 1,137,255 Progressive 44143
218 Illinois Riverwoods 1,123,810 Discover Financial 60015
219 California Santa Clara 1,122,844 Applied Materials 95054
220 California Santa Clara 1,122,844 Palo Alto Networks 95054
221 California Santa Clara 1,122,844 Advanced Micro Devices 95054
222 California Santa Clara 1,122,844 Nvidia 95051
223 California Santa Clara 1,122,844 ServiceNow 95054
224 California Santa Clara 1,122,844 Intel 95054
225 Nebraska Omaha 1,116,963 Union Pacific 68179
226 Nebraska Omaha 1,116,963 Peter Kiewit Sons' 68102
227 Nebraska Omaha 1,116,963 Mutual of Omaha Insurance 68175
228 Nebraska Omaha 1,116,963 Berkshire Hathaway 68131
229 Minnesota Minneapolis 1,108,596 General Mills 55426
230 Minnesota Minneapolis 1,108,596 U.S. Bancorp 55402
231 Minnesota Minneapolis 1,108,596 Xcel Energy 55401
232 Minnesota Minneapolis 1,108,596 Target 55403
233 Minnesota Minneapolis 1,108,596 Thrivent Financial for Lutherans 55415
234 Minnesota Minneapolis 1,108,596 Ameriprise Financial 55474
235 Michigan Dearborn 1,081,871 Ford Motor 48126
236 New York Victor 1,075,269 Constellation Brands 14564
237 Washington Redmond 1,075,000 Microsoft 98052
238 Florida Fort Lauderdale 1,067,729 AutoNation 33301
239 Michigan Bloomfield Hills 1,055,363 Penske Automotive 48302
240 Illinois North Chicago 1,023,636 AbbVie 60064
241 California San Francisco 1,023,212 Wells Fargo 94104
242 California San Francisco 1,023,212 Uber 94158
243 California San Francisco 1,023,212 Salesforce 94105
244 California San Francisco 1,023,212 Visa 94105
245 California San Francisco 1,023,212 Williams-Sonoma 94109
246 California San Francisco 1,023,212 Prologis 94111
247 California San Francisco 1,023,212 Gap 94105
248 California San Francisco 1,023,212 DoorDash 94107
249 California San Francisco 1,023,212 Airbnb 94103
250 Texas New Braunfels 987,342 Rush Enterprises 78130
251 California San Diego 986,470 Sempra 92101
252 California San Diego 986,470 Qualcomm 92121
253 California San Diego 986,470 LPL Financial s 92121
254 Louisiana New Orleans 967,480 Entergy 70113
255 California San Jose 943,023 Adobe 95110
256 California San Jose 943,023 PayPal 95131
257 California San Jose 943,023 Cisco Systems 95134
258 California San Jose 943,023 Ebay 95125
259 California San Jose 943,023 Sanmina 95134
260 California San Jose 943,023 Western Digital 95119
261 California San Jose 943,023 Super Micro Computer 95131
262 New York Tarrytown 940,397 Regeneron Pharmaceuticals 10591
263 Illinois Moline 931,532 Deere 61265
264 Ohio Orrville 911,111 J.M. Smucker 44667
265 Pennsylvania Allentown 904,418 PPL 18101
266 Pennsylvania Allentown 904,418 Air Products & Chemicals 18106
267 Michigan Jackson 903,614 CMS Energy 49201
268 North Carolina Charlotte 891,162 Truist Financial 28202
269 North Carolina Charlotte 891,162 Duke Energy 28202
270 North Carolina Charlotte 891,162 Bank of America 28255
271 North Carolina Charlotte 891,162 Honeywell 28202
272 North Carolina Charlotte 891,162 Nucor 28211
273 North Carolina Charlotte 891,162 Sonic Automotive 28211
274 Texas Round Rock 885,185 Dell Technologies 78682
275 New Jersey Rahway 867,568 Merck 07065
276 Massachusetts Cambridge 865,371 Biogen 02142
277 Massachusetts Cambridge 865,371 GE Vernova 02141
278 California Beverly Hills 854,339 Endeavor 90210
279 California Beverly Hills 854,339 Live Nation Entertainment 90210
280 Washington Bellevue 840,224 Paccar 98004
281 Washington Bellevue 840,224 Expeditors International of Washington 98006
282 Colorado Englewood 839,800 EchoStar 80112
283 Colorado Englewood 839,800 QVC 80112
284 California San Mateo 833,333 Franklin Resources 94403
285 Iowa Des Moines 817,259 Principal Financial 50392
286 Georgia Duluth 817,083 AGCO 30096
287 Georgia Duluth 817,083 Asbury Automotive 30097
288 Florida Jacksonville 813,394 GuideWell Mutual 32246
289 Florida Jacksonville 813,394 Fidelity National Information 32202
290 Florida Jacksonville 813,394 Fidelity National Financial 32204
291 Florida Jacksonville 813,394 CSX 32202
292 Texas Westlake 809,969 Charles Schwab 76262
293 Arizona Tempe 787,356 Carvana 85281
294 Kentucky Louisville 778,332 Humana 40202
295 Kentucky Louisville 778,332 BrightSpring Health Services 40222
296 Kentucky Louisville 778,332 Yum Brands 40213
297 Washington Issaquah 764,264 Costco 98027
298 Illinois Oak Brook 760,000 Ace Hardware 60523
299 Arizona Phoenix 757,793 Avnet 85034
300 Arizona Phoenix 757,793 Sprouts Farmers Market 85054
301 Arizona Phoenix 757,793 Republic Services 85054
302 Arizona Phoenix 757,793 Freeport-McMoRan 85004
303 Colorado Westminster 756,250 Ball 80021
304 Rhode Island Providence 738,370 Citizens Financial 02903
305 Rhode Island Providence 738,370 Textron 02903
306 Rhode Island Providence 738,370 United Natural Foods 02908
307 Minnesota St. Paul 730,456 Securian Financial 55101
308 Minnesota St. Paul 730,456 Ecolab 55102
309 Minnesota St. Paul 730,456 3M 55144
310 Ohio Evendale 730,189 General Electric 45215
311 Virginia Arlington 724,049 AES 22203
312 Virginia Arlington 724,049 RTX 22209
313 Virginia Arlington 724,049 Boeing 22202
314 Georgia Atlanta 711,349 Genuine Parts 30339
315 Georgia Atlanta 711,349 Southern 30308
316 Georgia Atlanta 711,349 Home Depot 30339
317 Georgia Atlanta 711,349 Coca-Cola 30313
318 Georgia Atlanta 711,349 Pulte 30326
319 Georgia Atlanta 711,349 Norfolk Southern 30308
320 Georgia Atlanta 711,349 Delta Airlines 30354
321 Georgia Atlanta 711,349 Assurant 30339
322 Georgia Atlanta 711,349 Intercontinental Exchange 30328
323 Georgia Atlanta 711,349 Global Payments 30326
324 Georgia Atlanta 711,349 Graphic Packaging 30328
325 Georgia Atlanta 711,349 Newell Brands 30328
326 Georgia Atlanta 711,349 UPS 30328
327 New Jersey Summit 704,545 Kenvue 07901
328 Connecticut Stamford 699,383 Philip Morris 06901
329 Connecticut Stamford 699,383 Charter Communications 06902
330 Connecticut Stamford 699,383 United Rentals 06902
331 Connecticut Stamford 699,383 Synchrony Financial 06902
332 Illinois Chicago 677,019 United Airlines 60606
333 Illinois Chicago 677,019 Kraft Heinz 60601
334 Illinois Chicago 677,019 Jones Lang LaSalle 60601
335 Illinois Chicago 677,019 Archer Daniels Midland 60601
336 Illinois Chicago 677,019 Conagra Brands 60654
337 Illinois Chicago 677,019 Old Republic International 60601
338 Illinois Chicago 677,019 Motorola Solutions 60661
339 Illinois Chicago 677,019 McDonald's 60607
340 Illinois Chicago 677,019 Molson Coors Beverage 60606
341 Illinois Chicago 677,019 Mondelez 60607
342 Illinois Chicago 677,019 Exelon 60603
343 Illinois Chicago 677,019 GE HealthCare Technologies 60661
344 Illinois Chicago 677,019 Northern Trust 60603
345 Illinois Chicago 677,019 Kellanova 60654
346 Tennessee Kingsport 671,429 Eastman Chemical 37660
347 Connecticut Norwalk 670,362 EMCOR 06851
348 Connecticut Norwalk 670,362 Booking s 06854
349 Ohio Akron 667,426 Goodyear Tire & Rubber 44316
350 Ohio Akron 667,426 FirstEnergy 44308
351 New Jersey Camden 666,667 Campbell's 08103
352 Florida Sunny Isles Beach 666,667 Icahn Enterprises 33160
353 Florida Plantation 661,111 Chewy 33322
354 Illinois Westchester 660,714 Ingredion 60154
355 Florida Tampa 658,696 Crown s 33637
356 Florida Tampa 658,696 Mosaic 33602
357 Kansas Merriam 650,000 Seaboard 66202
358 California Milpitas 649,007 KLA 95035
359 New York Long Island City 647,693 Altice USA 11101
360 New York Long Island City 647,693 JetBlue Airways 11101
361 Oregon Beaverton 647,355 Nike 97005
362 New Jersey New Brunswick 643,012 Johnson & Johnson 08933
363 Michigan Byron Center 633,333 SpartanNash 49315
364 Pennsylvania Pittsburgh 618,757 WESCO International 15219
365 Pennsylvania Pittsburgh 618,757 Westinghouse Air Brake Technologies 15212
366 Pennsylvania Pittsburgh 618,757 Alcoa 15212
367 Pennsylvania Pittsburgh 618,757 United States Steel 15219
368 Pennsylvania Pittsburgh 618,757 PPG Industries 15272
369 Pennsylvania Pittsburgh 618,757 Howmet Aerospace 15212
370 Pennsylvania Pittsburgh 618,757 PNC 15222
371 Illinois Lake Forest 616,727 Packaging Corp. of America 60045
372 Illinois Lake Forest 616,727 W.W. Grainger 60045
373 New York Buffalo 610,860 M&T Bank 14203
374 Virginia Glen Allen 607,876 Owens & Minor 23060
375 Virginia Glen Allen 607,876 Markel 23060
376 California Redwood City 597,225 Electronic Arts 94065
377 California Redwood City 597,225 Equinix 94065
378 California Manhattan Beach 596,026 Skechers U.S.A. 90266
379 Minnesota Austin 595,000 Hormel Foods 55912
380 Virginia Reston 583,503 Science Applications International 20190
381 Virginia Reston 583,503 CACI International 20190
382 Virginia Reston 583,503 NVR 20190
383 Virginia Reston 583,503 Leidos s 20190
384 Virginia Reston 583,503 General Dynamics 20190
385 Pennsylvania Hershey 580,311 Hershey 17033
386 Wisconsin Oshkosh 578,378 Oshkosh 54902
387 Texas Austin 555,290 Tesla 78725
388 Texas Austin 555,290 Oracle 78741
389 Virginia Newport News 553,539 Ferguson 23606
390 Virginia Newport News 553,539 Huntington Ingalls Industries 23607
391 Alabama Birmingham 548,129 Regions Financial 35203
392 Alabama Birmingham 548,129 Vulcan Materials 35242
393 North Carolina Raleigh 547,068 Advance Auto Parts 27609
394 North Carolina Raleigh 547,068 First Citizens BancShares 27609
395 New York Purchase 543,477 Mastercard 10577
396 New York Purchase 543,477 PepsiCo 10577
397 California Sunnyvale 538,462 Intuitive Surgical 94086
398 Louisiana Monroe 524,000 Lumen Technologies 71203
399 Massachusetts Burlington 523,810 Keurig Dr Pepper 01803
400 Florida Palm Beach Gardens 516,667 Carrier Global 33418
401 Delaware Wilmington 516,667 DuPont 19805
402 New York Melville 508,000 Henry Schein 11747
403 Florida St. Petersburg 496,815 Jabil 33716
404 Florida St. Petersburg 496,815 Raymond James Financial 33716
405 Illinois Deerfield 491,159 Baxter International 60015
406 Illinois Deerfield 491,159 Walgreens 60015
407 Indiana Columbus 489,943 Cummins 47201
408 Minnesota Richfield 488,235 Best Buy 55423
409 Arizona Chandler 474,599 Insight Enterprises 85286
410 Arizona Chandler 474,599 Microchip Technology 85224
411 Ohio Cleveland 470,144 TransDigm 44115
412 Ohio Cleveland 470,144 KeyCorp 44114
413 Ohio Cleveland 470,144 Cleveland-Cliffs 44114
414 Ohio Cleveland 470,144 Parker-Hannifin 44124
415 Ohio Cleveland 470,144 Sherwin-Williams 44115
416 Massachusetts Marlborough 468,153 BJ's Wholesale Club 01752
417 Massachusetts Marlborough 468,153 Boston Scientific 01752
418 Idaho Boise 462,883 Micron Technology 83716
419 Idaho Boise 462,883 Albertsons 83706
420 Pennsylvania Canonsburg 459,375 Viatris 15317
421 Florida Melbourne 453,191 L3Harris Technologies 32919
422 Indiana Warsaw 452,941 Zimmer Biomet s 46580
423 Iowa Ankeny 450,151 Casey's General Stores 50021
424 Indiana Elkhart 448,430 THOR Industries 46514
425 California Burbank 445,854 Walt Disney 91521
426 Michigan Livonia 433,333 Masco 48152
427 Michigan Portage 426,415 Stryker 49002
428 Virginia Falls Church 422,680 Northrop Grumman 22042
429 California Pleasanton 409,756 Workday 94588
430 Texas Fort Worth 406,602 American Airlines 76155
431 Washington Seattle 398,315 Expedia 98119
432 Washington Seattle 398,315 Nordstrom 98101
433 Washington Seattle 398,315 Coupang 98101
434 Washington Seattle 398,315 Starbucks 98134
435 Washington Seattle 398,315 Amazon 98109
436 Washington Seattle 398,315 Alaska Air 98188
437 Massachusetts Wilmington 391,667 Analog Devices 01887
438 North Carolina Mooresville 388,399 Lowe's 28117
439 Arkansas Springdale 386,232 Tyson Foods 72762
440 Minnesota Maplewood 377,273 Solventum 55144
441 Michigan Benton Harbor 377,273 Whirlpool 49022
442 Maryland Bethesda 374,356 Marriott International 20814
443 Maryland Bethesda 374,356 Lockheed Martin 20817
444 Pennsylvania Philadelphia 372,456 Comcast 19103
445 Pennsylvania Philadelphia 372,456 Aramark 19103
446 Illinois Abbott Park 368,421 Abbott Laboratories 60064
447 Illinois Glenview 361,364 Illinois Tool Works 60025
448 Arkansas Lowell 360,119 J.B. Hunt Transport Services 72745
449 Pennsylvania Coraopolis 358,289 Dick's Sporting Goods 15108
450 Minnesota Winona 357,143 Fastenal 55987
451 Illinois Downers Grove 350,000 Dover 60515
452 Florida Estero 346,154 Hertz 33928
453 Arkansas Bentonville 324,286 Walmart 72712
454 Connecticut New Britain 317,526 Stanley Black & Decker 06053
455 Florida Coral Gables 316,448 Ryder System 33134
456 Florida Coral Gables 316,448 MasTec 33134
457 Tennessee Antioch 306,383 LKQ 37013
458 New Jersey Roseland 300,000 Automatic Data Processing 07068
459 Tennessee Memphis 298,002 International Paper 38197
460 Tennessee Memphis 298,002 AutoZone 38103
461 Tennessee Memphis 298,002 FedEx 38120
462 Missouri Des Peres 296,364 Edward Jones 63131
463 Indiana Evansville 292,857 Berry Global 47710
464 Illinois Bolingbrook 289,744 Ulta Beauty 60440
465 New Jersey Franklin Lakes 272,973 Becton Dickinson 07417
466 Washington Sumner 271,795 Lululemon athletica 98390
467 Wisconsin Menomonee Falls 270,000 Kohl's 53051
468 Michigan Auburn Hills 267,540 Autoliv 48326
469 Michigan Auburn Hills 267,540 BorgWarner 48326
470 Nevada Las Vegas 265,535 Las Vegas Sands 89113
471 Nevada Las Vegas 265,535 MGM Resorts International 89109
472 Tennessee Nashville 260,517 HCA Healthcare 37203
473 Ohio Westerville 258,065 Vertiv s 43082
474 Georgia Calhoun 257,757 Mohawk Industries 30701
475 Ohio Mentor 251,429 Avery Dennison 44060
476 Tennessee Franklin 240,000 Community Health Systems 37067
477 Florida Lakeland 236,078 Publix Super Markets 33811
478 New York Corning 232,682 Corning 14831
479 Nevada Reno 226,000 Caesars Entertainment 89501
480 New Jersey Burlington 224,101 Burlington Stores 08016
481 New York Armonk 220,738 IBM 10504
482 Virginia Chesapeake 220,630 Dollar Tree 23320
483 Tennessee Goodlettsville 209,063 Dollar General 37072
484 Illinois Rolling Meadows 207,143 Arthur J. Gallagher 60008
485 North Carolina Burlington 198,777 Labcorp s 27215
486 Connecticut Farmington 198,611 Otis Worldwide 06032
487 California Dublin 197,196 Ross Stores 94568
488 New Jersey Secaucus 196,040 Quest Diagnostics 07094
489 Missouri Springfield 195,093 O'Reilly Automotive 65802
490 Pennsylvania King of Prussia 180,571 Universal Health Services 19406
491 North Carolina Durham 175,000 IQVIA s 27703
492 Massachusetts Framingham 154,945 TJX 01701
493 Michigan Southfield 134,139 Lear 48033
494 Connecticut Wallingford 121,600 Amphenol 06492
495 Virginia Ashburn 105,385 DXC Technology 20147
496 Florida Orlando 59,655 Darden Restaurants 32837
497 New Jersey Teaneck 58,492 Cognizant Technology 07666
498 Texas Plano 46,029 Yum China s 75074
499 California Newark 21,333 Concentrix 94560
In [199]:
gdfusactavreff = gdfusact.merge(dfctavreff, how = 'inner', on = ['Zip Code'])
gdfusactavreff = gdfusactavreff.sort_values('Efficiency', ascending=False).reset_index(drop=True)
In [200]:
mctavreff = gdfusactavreff.explore(column='Efficiency', name='The Average Efficiency in each City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mctavreff)
mctavreff
Out[200]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 

Statistics in Industry Level¶

In [59]:
# Grab all distinct Industry names
dfins = df[['Industry']]
dfins = dfins.drop_duplicates()
dfins = dfins.reset_index(drop=True)
inslist = dfins.to_numpy().tolist()
inslist[1][0]

for ins in inslist:
    print(ins[0])
    print("---------------")
General Merchandisers
---------------
Internet Services and Retailing
---------------
Health Care: Insurance and Managed Care
---------------
Computers, Office Equipment
---------------
Health Care: Pharmacy and Other Services
---------------
Insurance: Property and Casualty (Stock)
---------------
Petroleum Refining
---------------
Wholesalers: Health Care
---------------
Commercial Banks
---------------
Computer Software
---------------
Motor Vehicles & Parts
---------------
Specialty Retailers: Other
---------------
Diversified Financials
---------------
Food & Drug Stores
---------------
Telecommunications
---------------
Semiconductors and Other Electronic Components
---------------
Insurance: Property and Casualty (Mutual)
---------------
Food Consumer Products
---------------
Entertainment
---------------
Mail, Package and Freight Delivery
---------------
Pharmaceuticals
---------------
Food Production
---------------
Household and Personal Products
---------------
Pipelines
---------------
Aerospace & Defense
---------------
Wholesalers: Food and Grocery
---------------
Insurance: Life, Health (Stock)
---------------
Health Care: Medical Facilities
---------------
Construction and Farm Machinery
---------------
Information Technology Services
---------------
Insurance: Life, Health (Mutual)
---------------
Airlines
---------------
Wholesalers: Electronics and Office Equipment
---------------
Mining, Crude-Oil Production
---------------
Specialty Retailers: Apparel
---------------
Network and Other Communications Equipment
---------------
Apparel
---------------
Beverages
---------------
Chemicals
---------------
Scientific, Photographic and Control Equipment
---------------
Energy
---------------
Medical Products and Equipment
---------------
Industrial Machinery
---------------
Tobacco
---------------
Homebuilders
---------------
Automotive Retailing, Services
---------------
Food Services
---------------
Financial Data Services
---------------
Real Estate
---------------
Metals
---------------
Utilities: Gas and Electric
---------------
Securities
---------------
Wholesalers: Diversified
---------------
Oil and Gas Equipment, Services
---------------
Hotels, Casinos, Resorts
---------------
Railroads
---------------
Engineering & Construction
---------------
Waste Management
---------------
Diversified Outsourcing Services
---------------
Packaging, Containers
---------------
Transportation and Logistics
---------------
Electronics, Electrical Equip.
---------------
Building Materials, Glass
---------------
Advertising, Marketing
---------------
Trucking, Truck Leasing
---------------
Home Equipment, Furnishings
---------------
Publishing, Printing
---------------
In [ ]:
 
In [61]:
# Check the Largest Revenue Company in each Industry
dfinsmaxrevco = df.head(1)

for ins in inslist[0:]:
    dfin = df.where(df['Industry'] == ins[0]).dropna()
    mninmaxrev = dfin['Revenue (rounded)'].max()
    dfinmaxrevco = dfin.where(dfin['Revenue (rounded)'] == mninmaxrev).dropna()
    dfinsmaxrevco = pd.concat([dfinsmaxrevco, dfinmaxrevco], ignore_index=True)
    
dfinsmaxrevco = dfinsmaxrevco.drop(0)
dfinsmaxrevco[['Industry','State','City','Company','Zip Code','Revenue (rounded)']].sort_values(by='Revenue (rounded)', ascending=False).reset_index(drop=True)
Out[61]:
Industry State City Company Zip Code Revenue (rounded)
0 General Merchandisers Arkansas Bentonville Walmart 72712 681,000,000,000
1 Internet Services and Retailing Washington Seattle Amazon 98109 638,000,000,000
2 Health Care: Insurance and Managed Care Minnesota Eden Prairie UnitedHealth 55344 400,300,000,000
3 Computers, Office Equipment California Cupertino Apple 95014 391,000,000,000
4 Health Care: Pharmacy and Other Services Rhode Island Woonsocket CVS Health 02895 372,800,000,000
5 Insurance: Property and Casualty (Stock) Nebraska Omaha Berkshire Hathaway 68131 371,400,000,000
6 Petroleum Refining Texas Spring Exxon Mobil 77389 349,600,000,000
7 Wholesalers: Health Care Texas Irving McKesson 75039 309,000,000,000
8 Commercial Banks New York New York JPMorgan Chase 10017 278,900,000,000
9 Computer Software Washington Redmond Microsoft 98052 245,100,000,000
10 Motor Vehicles & Parts Michigan Detroit General Motors 48265 187,400,000,000
11 Specialty Retailers: Other Georgia Atlanta Home Depot 30339 159,500,000,000
12 Diversified Financials District of Columbia Washington Fannie Mae 20005 152,700,000,000
13 Food & Drug Stores Illinois Deerfield Walgreens 60015 147,700,000,000
14 Telecommunications New York New York Verizon 10036 134,800,000,000
15 Semiconductors and Other Electronic Components California Santa Clara Nvidia 95051 130,500,000,000
16 Insurance: Property and Casualty (Mutual) Illinois Bloomington State Farm 61710 123,000,000,000
17 Food Consumer Products New York Purchase PepsiCo 10577 91,900,000,000
18 Entertainment California Burbank Walt Disney 91521 91,400,000,000
19 Mail, Package and Freight Delivery Georgia Atlanta UPS 30328 91,100,000,000
20 Pharmaceuticals New Jersey New Brunswick Johnson & Johnson 08933 88,800,000,000
21 Food Production Illinois Chicago Archer Daniels Midland 60601 85,500,000,000
22 Household and Personal Products Ohio Cincinnati Procter & Gamble 45202 84,000,000,000
23 Pipelines Texas Dallas Energy Transfer 75225 82,700,000,000
24 Aerospace & Defense Virginia Arlington RTX 22209 80,700,000,000
25 Wholesalers: Food and Grocery Texas Houston Sysco 77077 78,800,000,000
26 Insurance: Life, Health (Stock) New York New York MetLife 10166 71,000,000,000
27 Health Care: Medical Facilities Tennessee Nashville HCA Healthcare 37203 70,600,000,000
28 Construction and Farm Machinery Texas Irving Caterpillar 75039 64,800,000,000
29 Information Technology Services New York Armonk IBM 10504 62,800,000,000
30 Insurance: Life, Health (Mutual) New York New York New York Life Insurance 10010 62,600,000,000
31 Airlines Georgia Atlanta Delta Airlines 30354 61,600,000,000
32 Wholesalers: Electronics and Office Equipment California Fremont TD Synnex 94538 58,500,000,000
33 Mining, Crude-Oil Production Texas Houston ConocoPhillips 77079 57,000,000,000
34 Specialty Retailers: Apparel Massachusetts Framingham TJX 01701 56,400,000,000
35 Network and Other Communications Equipment California San Jose Cisco Systems 95134 53,800,000,000
36 Apparel Oregon Beaverton Nike 97005 51,400,000,000
37 Beverages Georgia Atlanta Coca-Cola 30313 47,100,000,000
38 Chemicals Michigan Midland Dow 48674 43,000,000,000
39 Scientific, Photographic and Control Equipment Massachusetts Waltham Thermo Fisher Scientific 02451 42,900,000,000
40 Energy Florida Miami World Kinect 33178 42,200,000,000
41 Medical Products and Equipment Illinois Abbott Park Abbott Laboratories 60064 42,000,000,000
42 Industrial Machinery North Carolina Charlotte Honeywell 28202 38,500,000,000
43 Tobacco Connecticut Stamford Philip Morris 06901 37,900,000,000
44 Homebuilders Texas Arlington D.R. Horton 76011 36,800,000,000
45 Automotive Retailing, Services Oregon Medford Lithia Motors 97501 36,600,000,000
46 Food Services Washington Seattle Starbucks 98134 36,200,000,000
47 Financial Data Services California San Francisco Visa 94105 35,900,000,000
48 Real Estate Texas Dallas CBRE 75201 35,800,000,000
49 Metals North Carolina Charlotte Nucor 28211 30,700,000,000
50 Securities New York New York KKR 10001 29,900,000,000
51 Utilities: Gas and Electric North Carolina Charlotte Duke Energy 28202 29,900,000,000
52 Wholesalers: Diversified Virginia Newport News Ferguson 23606 29,600,000,000
53 Oil and Gas Equipment, Services Texas Houston Baker Hughes 77079 27,800,000,000
54 Hotels, Casinos, Resorts Maryland Bethesda Marriott International 20814 25,100,000,000
55 Railroads Nebraska Omaha Union Pacific 68179 24,200,000,000
56 Engineering & Construction Texas Houston Quanta Services 77008 23,700,000,000
57 Waste Management Texas Houston Waste Management 77002 22,100,000,000
58 Diversified Outsourcing Services New Jersey Roseland Automatic Data Processing 07068 19,200,000,000
59 Packaging, Containers Tennessee Memphis International Paper 38197 18,600,000,000
60 Transportation and Logistics Minnesota Eden Prairie C.H. Robinson Worldwide 55347 17,700,000,000
61 Electronics, Electrical Equip. Michigan Benton Harbor Whirlpool 49022 16,600,000,000
62 Building Materials, Glass Texas Irving Builders FirstSource 75039 16,400,000,000
63 Advertising, Marketing New York New York Omnicom 10017 15,700,000,000
64 Trucking, Truck Leasing Arkansas Lowell J.B. Hunt Transport Services 72745 12,100,000,000
65 Home Equipment, Furnishings Georgia Calhoun Mohawk Industries 30701 10,800,000,000
66 Publishing, Printing New York New York News Corp. 10036 10,100,000,000
In [62]:
# Join the Dataframe 'gdfusact' with 'dfinsmaxrevco' for the Largest Revenue Company in each Industry visualized by City
gdfusactinsmaxrevco = gdfusact.merge(dfinsmaxrevco, how = 'inner', on = ['Zip Code'])
gdfusactinsmaxrevco = gdfusactinsmaxrevco.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [63]:
# Join the Dataframe 'gdfsts' with 'dfinsmaxrevco' for the Largest Revenue Company in each Industry visualized by State
gdfstsinsmaxrevco = gdfsts.merge(dfinsmaxrevco, how = 'inner', on = ['State'])
gdfstsinsmaxrevco = gdfstsinsmaxrevco.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [64]:
# Draw multi-layer Map visualizing The Largest Revenue Company in each Industry by City and State
minsmaxrc = gdfstsinsmaxrevco.explore(column='Revenue (rounded)', name='The Largest Revenue Company in each Industry visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactinsmaxrevco.explore(m=minsmaxrc, column='Revenue (rounded)', name='The Largest Revenue Company in each Industry visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(minsmaxrc)
minsmaxrc
Out[64]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [66]:
# Check the Smallest Revenue Company in each Industry
dfinsminrevco = df.head(1)

for ins in inslist[0:]:
    dfin = df.where(df['Industry'] == ins[0]).dropna()
    mninsminrev = dfin['Revenue (rounded)'].min()
    dfinminrevco = dfin.where(dfin['Revenue (rounded)'] == mninsminrev).dropna()
    dfinsminrevco = pd.concat([dfinsminrevco, dfinminrevco], ignore_index=True)
    
dfinsminrevco = dfinsminrevco.drop(0)
dfinsminrevco[['Industry','State','City','Company','Zip Code','Revenue (rounded)']].sort_values(by='Revenue (rounded)', ascending=False).reset_index(drop=True)
Out[66]:
Industry State City Company Zip Code Revenue (rounded)
0 Mail, Package and Freight Delivery Tennessee Memphis FedEx 38120 87,700,000,000
1 Scientific, Photographic and Control Equipment Massachusetts Waltham Thermo Fisher Scientific 02451 42,900,000,000
2 Wholesalers: Electronics and Office Equipment Arizona Phoenix Avnet 85034 23,800,000,000
3 Tobacco Virginia Richmond Altria 23230 20,400,000,000
4 Energy Texas Irving Vistra 75039 17,200,000,000
5 Energy Massachusetts Waltham Global Partners 02453 17,200,000,000
6 Waste Management Arizona Phoenix Republic Services 85054 16,000,000,000
7 Household and Personal Products New Jersey Summit Kenvue 07901 15,500,000,000
8 General Merchandisers Washington Seattle Nordstrom 98101 15,000,000,000
9 Insurance: Property and Casualty (Mutual) Pennsylvania Erie Erie Insurance 16530 13,200,000,000
10 Computers, Office Equipment California San Jose Western Digital 95119 13,000,000,000
11 Health Care: Medical Facilities Tennessee Franklin Community Health Systems 37067 12,600,000,000
12 Engineering & Construction Florida Coral Gables MasTec 33134 12,300,000,000
13 Railroads Georgia Atlanta Norfolk Southern 30308 12,100,000,000
14 Trucking, Truck Leasing Arkansas Lowell J.B. Hunt Transport Services 72745 12,100,000,000
15 Hotels, Casinos, Resorts Virginia McLean Hilton 22102 11,200,000,000
16 Insurance: Life, Health (Mutual) Minnesota Minneapolis Thrivent Financial for Lutherans 55415 10,900,000,000
17 Wholesalers: Health Care Virginia Glen Allen Owens & Minor 23060 10,700,000,000
18 Advertising, Marketing New York New York Interpublic 10022 10,700,000,000
19 Construction and Farm Machinery Wisconsin Oshkosh Oshkosh 54902 10,700,000,000
20 Pipelines Oklahoma Tulsa Williams 74172 10,500,000,000
21 Financial Data Services Georgia Atlanta Global Payments 30326 10,100,000,000
22 Publishing, Printing New York New York News Corp. 10036 10,100,000,000
23 Internet Services and Retailing Colorado Englewood QVC 80112 10,000,000,000
24 Motor Vehicles & Parts Indiana Elkhart THOR Industries 46514 10,000,000,000
25 Health Care: Pharmacy and Other Services New Jersey Secaucus Quest Diagnostics 07094 9,900,000,000
26 Wholesalers: Food and Grocery Michigan Byron Center SpartanNash 49315 9,500,000,000
27 Chemicals Tennessee Kingsport Eastman Chemical 37660 9,400,000,000
28 Airlines New York Long Island City JetBlue Airways 11101 9,300,000,000
29 Pharmaceuticals New Jersey Parsippany Zoetis 07054 9,300,000,000
30 Commercial Banks Ohio Cleveland KeyCorp 44114 9,200,000,000
31 Health Care: Insurance and Managed Care New York New York Oscar Health 10013 9,200,000,000
32 Mining, Crude-Oil Production Colorado Denver Ovintiv 80202 9,200,000,000
33 Telecommunications New York Long Island City Altice USA 11101 9,000,000,000
34 Oil and Gas Equipment, Services Texas Houston NOV 77042 8,900,000,000
35 Apparel New York New York PVH 10017 8,700,000,000
36 Securities California San Mateo Franklin Resources 94403 8,500,000,000
37 Industrial Machinery Illinois Downers Grove Dover 60515 8,400,000,000
38 Computer Software California Pleasanton Workday 94588 8,400,000,000
39 Diversified Outsourcing Services New York New York ABM Industries 10006 8,400,000,000
40 Packaging, Containers Illinois Lake Forest Packaging Corp. of America 60045 8,400,000,000
41 Insurance: Property and Casualty (Stock) Illinois Chicago Old Republic International 60601 8,200,000,000
42 Homebuilders Arizona Scottsdale Taylor Morrison Home 85251 8,200,000,000
43 Insurance: Life, Health (Stock) Minnesota St. Paul Securian Financial 55101 8,200,000,000
44 Transportation and Logistics Connecticut Greenwich XPO 06831 8,100,000,000
45 Petroleum Refining Texas Houston Par Pacific 77024 8,000,000,000
46 Electronics, Electrical Equip. Ohio Westerville Vertiv s 43082 8,000,000,000
47 Real Estate Ohio Toledo Welltower 43615 8,000,000,000
48 Network and Other Communications Equipment California Santa Clara Palo Alto Networks 95054 8,000,000,000
49 Specialty Retailers: Apparel New York New York Foot Locker 10001 8,000,000,000
50 Diversified Financials New York New York Voya Financial 10169 8,000,000,000
51 Metals Texas Irving Commercial Metals 75039 7,900,000,000
52 Food Consumer Products Missouri St. Louis Post s 63144 7,900,000,000
53 Automotive Retailing, Services Texas New Braunfels Rush Enterprises 78130 7,800,000,000
54 Medical Products and Equipment Indiana Warsaw Zimmer Biomet s 46580 7,700,000,000
55 Food & Drug Stores Arizona Phoenix Sprouts Farmers Market 85054 7,700,000,000
56 Home Equipment, Furnishings Georgia Atlanta Newell Brands 30328 7,600,000,000
57 Semiconductors and Other Electronic Components Arizona Chandler Microchip Technology 85224 7,600,000,000
58 Semiconductors and Other Electronic Components California San Jose Sanmina 95134 7,600,000,000
59 Specialty Retailers: Other Virginia Richmond ARKO 23227 7,600,000,000
60 Information Technology Services Virginia Reston Science Applications International 20190 7,500,000,000
61 Entertainment California Beverly Hills Endeavor 90210 7,500,000,000
62 Utilities: Gas and Electric Michigan Jackson CMS Energy 49201 7,500,000,000
63 Beverages California Corona Monster Beverage 92879 7,500,000,000
64 Food Services Kentucky Louisville Yum Brands 40213 7,500,000,000
65 Wholesalers: Diversified Missouri St. Louis Core & Main 63146 7,400,000,000
66 Building Materials, Glass Alabama Birmingham Vulcan Materials 35242 7,400,000,000
67 Aerospace & Defense Pennsylvania Pittsburgh Howmet Aerospace 15212 7,400,000,000
68 Food Production Illinois Westchester Ingredion 60154 7,400,000,000
In [67]:
# Join the Dataframe 'gdfusact' with 'dfinsminrevco' for the Smallest Revenue Company in each Industry visualized by City
gdfusactinsminrevco = gdfusact.merge(dfinsminrevco, how = 'inner', on = ['Zip Code'])
gdfusactinsminrevco = gdfusactinsminrevco.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [68]:
# Join the Dataframe 'gdfsts' with 'dfinsminrevco' for the Smallest Revenue Company in each Industry visualized by State
gdfstsinsminrevco = gdfsts.merge(dfinsminrevco, how = 'inner', on = ['State'])
gdfstsinsminrevco = gdfstsinsminrevco.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [69]:
minsminrc = gdfstsinsminrevco.explore(column='Revenue (rounded)', name='The Smallest Revenue Company in each Industry visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactinsminrevco.explore(m=minsminrc, column='Revenue (rounded)', name='The Smallest Revenue Company in each Industry visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(minsminrc)
minsminrc
Out[69]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [82]:
# Check the Biggest Revenue Industry in US (a.k.a Total Revenue in each Industry)
dfintr = df.groupby('Industry', as_index=False)[['Revenue (rounded)']].sum('Revenue (rounded)').sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
dfintr
Out[82]:
Industry Revenue (rounded)
0 Internet Services and Retailing 1,330,100,000,000
1 Commercial Banks 1,321,000,000,000
2 General Merchandisers 1,116,800,000,000
3 Petroleum Refining 1,044,500,000,000
4 Health Care: Insurance and Managed Care 908,000,000,000
5 Wholesalers: Health Care 853,200,000,000
6 Insurance: Property and Casualty (Stock) 842,900,000,000
7 Health Care: Pharmacy and Other Services 669,500,000,000
8 Diversified Financials 627,600,000,000
9 Computers, Office Equipment 598,300,000,000
10 Motor Vehicles & Parts 590,800,000,000
11 Specialty Retailers: Other 505,200,000,000
12 Pharmaceuticals 487,300,000,000
13 Telecommunications 473,800,000,000
14 Semiconductors and Other Electronic Components 446,900,000,000
15 Food & Drug Stores 441,900,000,000
16 Aerospace & Defense 407,400,000,000
17 Computer Software 393,200,000,000
18 Utilities: Gas and Electric 329,200,000,000
19 Insurance: Life, Health (Stock) 299,200,000,000
20 Pipelines 268,400,000,000
21 Food Consumer Products 263,800,000,000
22 Entertainment 259,900,000,000
23 Insurance: Life, Health (Mutual) 249,800,000,000
24 Insurance: Property and Casualty (Mutual) 226,100,000,000
25 Food Production 222,800,000,000
26 Airlines 221,400,000,000
27 Automotive Retailing, Services 215,700,000,000
28 Wholesalers: Food and Grocery 211,900,000,000
29 Mining, Crude-Oil Production 210,700,000,000
30 Industrial Machinery 207,800,000,000
31 Chemicals 203,000,000,000
32 Information Technology Services 201,900,000,000
33 Medical Products and Equipment 184,600,000,000
34 Mail, Package and Freight Delivery 178,800,000,000
35 Securities 175,900,000,000
36 Financial Data Services 175,300,000,000
37 Wholesalers: Diversified 169,600,000,000
38 Energy 163,200,000,000
39 Wholesalers: Electronics and Office Equipment 158,200,000,000
40 Household and Personal Products 155,300,000,000
41 Construction and Farm Machinery 138,900,000,000
42 Health Care: Medical Facilities 132,500,000,000
43 Specialty Retailers: Apparel 121,800,000,000
44 Homebuilders 119,800,000,000
45 Metals 116,600,000,000
46 Food Services 103,600,000,000
47 Engineering & Construction 100,000,000,000
48 Real Estate 95,100,000,000
49 Beverages 91,600,000,000
50 Diversified Outsourcing Services 89,500,000,000
51 Network and Other Communications Equipment 87,800,000,000
52 Packaging, Containers 80,800,000,000
53 Apparel 79,600,000,000
54 Hotels, Casinos, Resorts 76,100,000,000
55 Transportation and Logistics 60,700,000,000
56 Oil and Gas Equipment, Services 59,600,000,000
57 Tobacco 58,300,000,000
58 Railroads 50,800,000,000
59 Electronics, Electrical Equip. 46,000,000,000
60 Scientific, Photographic and Control Equipment 42,900,000,000
61 Waste Management 38,100,000,000
62 Building Materials, Glass 34,800,000,000
63 Advertising, Marketing 26,400,000,000
64 Home Equipment, Furnishings 26,200,000,000
65 Trucking, Truck Leasing 12,100,000,000
66 Publishing, Printing 10,100,000,000
In [83]:
# Join the Dataframe 'gdfusact' with 'dfintr' for the Top 10
dfintr = dfintr.head(10).merge(df[['Industry','City','State','Company','Zip Code']], how = 'inner', on = ['Industry'])
gdfusactintr = gdfusact.merge(dfintr, how = 'inner', on = ['Zip Code'])
gdfusactintr = gdfusactintr.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)

# Join the Dataframe 'gdfsts' with 'dfintr'
gdfstsintr = gdfsts.merge(dfintr, how = 'inner', on = ['State'])
gdfstsintr = gdfstsintr.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [84]:
# Check what Companies that are in Industry 'Internet Services and Retailing'.
dfintr1st = dfintr.where(dfintr['Industry'] == 'Internet Services and Retailing').dropna()
dfintr1st
Out[84]:
Industry Revenue (rounded) City State Company Zip Code
0 Internet Services and Retailing 1,330,100,000,000 Seattle Washington Amazon 98109
1 Internet Services and Retailing 1,330,100,000,000 Mountain View California Alphabet 94043
2 Internet Services and Retailing 1,330,100,000,000 Menlo Park California Meta 94025
3 Internet Services and Retailing 1,330,100,000,000 San Francisco California Uber 94158
4 Internet Services and Retailing 1,330,100,000,000 Seattle Washington Coupang 98101
5 Internet Services and Retailing 1,330,100,000,000 Norwalk Connecticut Booking s 06854
6 Internet Services and Retailing 1,330,100,000,000 Seattle Washington Expedia 98119
7 Internet Services and Retailing 1,330,100,000,000 Plantation Florida Chewy 33322
8 Internet Services and Retailing 1,330,100,000,000 Boston Massachusetts Wayfair 02116
9 Internet Services and Retailing 1,330,100,000,000 San Francisco California Airbnb 94103
10 Internet Services and Retailing 1,330,100,000,000 San Francisco California DoorDash 94107
11 Internet Services and Retailing 1,330,100,000,000 San Jose California Ebay 95125
12 Internet Services and Retailing 1,330,100,000,000 Englewood Colorado QVC 80112
In [85]:
# Draw the Map visualizing Total Revenue in each Industry by State and City
minstr = gdfstsintr.explore(column='Revenue (rounded)', name='The Total Revenue in each Industry visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactintr.explore(m=minstr, column='Revenue (rounded)', name='The Total Revenue in each Industry visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(minstr)
minstr
Out[85]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [86]:
# Draw the Map visualizing the Companies that are in the Biggest Revenue Industry by State and City
gdfstsintr1st = gdfstsintr.where(gdfstsintr['Industry'] == 'Internet Services and Retailing').dropna()
gdfusactintr1st = gdfusactintr.where(gdfusactintr['Industry'] == 'Internet Services and Retailing').dropna()

minstr1st = gdfstsintr1st.explore(column='Revenue (rounded)', name='The Biggest Revenue Industry Companies visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactintr1st.explore(m=minstr1st, column='Revenue (rounded)', name='The Biggest Revenue Industry Companies visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(minstr1st)
minstr1st
Out[86]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [76]:
# Check the Average Revenue in each Industry (a.k.a The Biggest Average Revenue Industry in US)
dfinavr = df.groupby('Industry')[df.columns[[7]]].mean('Revenue (rounded)').sort_values('Revenue (rounded)', ascending=False)
dfinavr
Out[76]:
Revenue (rounded)
Industry
Wholesalers: Health Care 170,640,000,000
General Merchandisers 159,542,857,143
Health Care: Insurance and Managed Care 151,333,333,333
Petroleum Refining 116,055,555,556
Health Care: Pharmacy and Other Services 111,583,333,333
Internet Services and Retailing 102,315,384,615
Computers, Office Equipment 99,716,666,667
Mail, Package and Freight Delivery 89,400,000,000
Food & Drug Stores 88,380,000,000
Telecommunications 67,685,714,286
Commercial Banks 66,050,000,000
Motor Vehicles & Parts 59,080,000,000
Computer Software 56,171,428,571
Insurance: Property and Casualty (Stock) 46,827,777,778
Insurance: Property and Casualty (Mutual) 45,220,000,000
Scientific, Photographic and Control Equipment 42,900,000,000
Wholesalers: Food and Grocery 42,380,000,000
Diversified Financials 41,840,000,000
Wholesalers: Electronics and Office Equipment 39,550,000,000
Pharmaceuticals 37,484,615,385
Aerospace & Defense 37,036,363,636
Airlines 36,900,000,000
Construction and Farm Machinery 34,725,000,000
Pipelines 33,550,000,000
Semiconductors and Other Electronic Components 31,921,428,571
Food Production 31,828,571,429
Specialty Retailers: Other 31,575,000,000
Insurance: Life, Health (Mutual) 31,225,000,000
Household and Personal Products 31,060,000,000
Tobacco 29,150,000,000
Entertainment 28,877,777,778
Energy 27,200,000,000
Insurance: Life, Health (Stock) 27,200,000,000
Health Care: Medical Facilities 26,500,000,000
Food Consumer Products 21,983,333,333
Network and Other Communications Equipment 21,950,000,000
Financial Data Services 21,912,500,000
Mining, Crude-Oil Production 21,070,000,000
Specialty Retailers: Apparel 20,300,000,000
Homebuilders 19,966,666,667
Apparel 19,900,000,000
Oil and Gas Equipment, Services 19,866,666,667
Automotive Retailing, Services 19,609,090,909
Waste Management 19,050,000,000
Industrial Machinery 18,890,909,091
Medical Products and Equipment 18,460,000,000
Beverages 18,320,000,000
Securities 17,590,000,000
Food Services 17,266,666,667
Railroads 16,933,333,333
Chemicals 16,916,666,667
Information Technology Services 16,825,000,000
Engineering & Construction 16,666,666,667
Metals 16,657,142,857
Real Estate 15,850,000,000
Utilities: Gas and Electric 15,676,190,476
Hotels, Casinos, Resorts 15,220,000,000
Diversified Outsourcing Services 14,916,666,667
Wholesalers: Diversified 14,133,333,333
Advertising, Marketing 13,200,000,000
Transportation and Logistics 12,140,000,000
Trucking, Truck Leasing 12,100,000,000
Building Materials, Glass 11,600,000,000
Packaging, Containers 11,542,857,143
Electronics, Electrical Equip. 11,500,000,000
Publishing, Printing 10,100,000,000
Home Equipment, Furnishings 8,733,333,333
In [77]:
# Join the Dataframe 'gdfusact' with 'dfinavr' for the Top 10
dfinavrall = dfinavr.merge(df[['Industry','City','State','Company','Zip Code']], how = 'inner', on = ['Industry'])
dfinavr10 = dfinavr.head(10).merge(df[['Industry','City','State','Company','Zip Code']], how = 'inner', on = ['Industry'])
gdfusactinavr = gdfusact.merge(dfinavr10, how = 'inner', on = ['Zip Code'])
gdfusactinavr = gdfusactinavr.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)

# Join the Dataframe 'gdfsts' with 'dfinavr'
gdfstsinavr = gdfsts.merge(dfinavr10, how = 'inner', on = ['State'])
gdfstsinavr = gdfstsinavr.sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
In [78]:
# Fun fact: turns out, there are other Companies that have exactly same ZipCode with McKesson in Irving, Texas.
# The impact on the map, McKesson company even doesn't show up.
dfinavrall.where(dfinavrall['Zip Code'] == '75039').dropna()
Out[78]:
Industry Revenue (rounded) City State Company Zip Code
0 Wholesalers: Health Care 170,640,000,000 Irving Texas McKesson 75039
181 Construction and Farm Machinery 34,725,000,000 Irving Texas Caterpillar 75039
258 Energy 27,200,000,000 Irving Texas Vistra 75039
397 Chemicals 16,916,666,667 Irving Texas Celanese 75039
413 Engineering & Construction 16,666,666,667 Irving Texas Fluor 75039
423 Metals 16,657,142,857 Irving Texas Commercial Metals 75039
482 Building Materials, Glass 11,600,000,000 Irving Texas Builders FirstSource 75039
In [79]:
# Draw the Map visualizing Average Revenue in each Industry by State and City
minsavr = gdfstsinavr.explore(column='Revenue (rounded)', name='The Average Revenue in each Industry visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactinavr.explore(m=minsavr, column='Revenue (rounded)', name='The Average Revenue in each Industry visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(minsavr)
minsavr
Out[79]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [80]:
# Draw the Map visualizing the Companies that are in the Biggest Average Revenue Industry by State and City
gdfstsinavr1st = gdfstsinavr.where(gdfstsinavr['Industry'] == 'Wholesalers: Health Care').dropna()
gdfusactinavr1st = gdfusactinavr.where(gdfusactinavr['Industry'] == 'Wholesalers: Health Care').dropna()

minsavr1st = gdfstsinavr1st.explore(column='Revenue (rounded)', name='The Biggest Average Revenue Industry Companies visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactinavr1st.explore(m=minsavr1st, column='Revenue (rounded)', name='The Biggest Average Revenue Industry Companies visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(minsavr1st)
minsavr1st
Out[80]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [88]:
# Check the Biggest Employer Company in each Industry
dfinsmaxempco = df.head(1)

for ins in inslist[0:]:
    dfin = df.where(df['Industry'] == ins[0]).dropna()
    mninsmaxemp = dfin['Employees'].max()
    dfinmaxempco = dfin.where(dfin['Employees'] == mninsmaxemp).dropna()
    dfinsmaxempco = pd.concat([dfinsmaxempco, dfinmaxempco], ignore_index=True)
    
dfinsmaxempco = dfinsmaxempco.drop(0)
dfinsmaxempco = dfinsmaxempco[['Industry','State','City','Company','Zip Code','Employees']].sort_values(by='Employees', ascending=False).reset_index(drop=True)
dfinsmaxempco
Out[88]:
Industry State City Company Zip Code Employees
0 General Merchandisers Arkansas Bentonville Walmart 72712 2,100,000
1 Internet Services and Retailing Washington Seattle Amazon 98109 1,556,000
2 Specialty Retailers: Other Georgia Atlanta Home Depot 30339 470,100
3 Information Technology Services California Newark Concentrix 94560 450,000
4 Mail, Package and Freight Delivery Tennessee Memphis FedEx 38120 422,100
5 Food & Drug Stores Ohio Cincinnati Kroger 45202 409,000
6 Health Care: Insurance and Managed Care Minnesota Eden Prairie UnitedHealth 55344 400,000
7 Insurance: Property and Casualty (Stock) Nebraska Omaha Berkshire Hathaway 68131 392,400
8 Specialty Retailers: Apparel Massachusetts Framingham TJX 01701 364,000
9 Food Services Washington Seattle Starbucks 98134 361,000
10 Food Consumer Products New York Purchase PepsiCo 10577 319,000
11 Commercial Banks New York New York JPMorgan Chase 10017 317,200
12 Health Care: Medical Facilities Tennessee Nashville HCA Healthcare 37203 271,000
13 Diversified Outsourcing Services Pennsylvania Philadelphia Aramark 19103 266,700
14 Health Care: Pharmacy and Other Services Rhode Island Woonsocket CVS Health 02895 259,500
15 Computer Software Washington Redmond Microsoft 98052 228,000
16 Entertainment California Burbank Walt Disney 91521 205,000
17 Aerospace & Defense Virginia Arlington RTX 22209 186,000
18 Telecommunications Pennsylvania Philadelphia Comcast 19103 182,000
19 Hotels, Casinos, Resorts Virginia McLean Hilton 22102 181,000
20 Motor Vehicles & Parts Michigan Southfield Lear 48033 173,700
21 Computers, Office Equipment California Cupertino Apple 95014 164,000
22 Real Estate Texas Dallas CBRE 75201 140,000
23 Pharmaceuticals New Jersey New Brunswick Johnson & Johnson 08933 138,100
24 Food Production Arkansas Springdale Tyson Foods 72762 138,000
25 Semiconductors and Other Electronic Components Florida St. Petersburg Jabil 33716 138,000
26 Airlines Texas Fort Worth American Airlines 76155 133,300
27 Transportation and Logistics Connecticut Greenwich GXO Logistics 06831 128,500
28 Scientific, Photographic and Control Equipment Massachusetts Waltham Thermo Fisher Scientific 02451 125,000
29 Network and Other Communications Equipment Connecticut Wallingford Amphenol 06492 125,000
30 Medical Products and Equipment Illinois Abbott Park Abbott Laboratories 60064 114,000
31 Construction and Farm Machinery Texas Irving Caterpillar 75039 112,900
32 Household and Personal Products Ohio Cincinnati Procter & Gamble 45202 108,000
33 Industrial Machinery North Carolina Charlotte Honeywell 28202 102,000
34 Diversified Financials New York New York Marsh & McLennan 10036 90,000
35 Tobacco Connecticut Stamford Philip Morris 06901 83,100
36 Apparel Oregon Beaverton Nike 97005 79,400
37 Energy Massachusetts Cambridge GE Vernova 02141 76,800
38 Wholesalers: Food and Grocery Texas Houston Sysco 77077 76,000
39 Advertising, Marketing New York New York Omnicom 10017 74,900
40 Beverages Georgia Atlanta Coca-Cola 30313 69,700
41 Insurance: Property and Casualty (Mutual) Illinois Bloomington State Farm 61710 67,400
42 Chemicals Ohio Cleveland Sherwin-Williams 44115 63,900
43 Wholesalers: Diversified Georgia Atlanta Genuine Parts 30339 63,000
44 Waste Management Texas Houston Waste Management 77002 61,700
45 Petroleum Refining Texas Spring Exxon Mobil 77389 60,900
46 Engineering & Construction Texas Houston Quanta Services 77008 58,400
47 Oil and Gas Equipment, Services Texas Houston Baker Hughes 77079 57,000
48 Electronics, Electrical Equip. New York Corning Corning 14831 56,300
49 Securities Missouri Des Peres Edward Jones 63131 55,000
50 Financial Data Services Florida Jacksonville Fidelity National Information 32202 50,000
51 Wholesalers: Health Care Ohio Dublin Cardinal Health 43017 48,400
52 Insurance: Life, Health (Stock) New York New York MetLife 10166 45,000
53 Packaging, Containers Indiana Evansville Berry Global 47710 42,000
54 Home Equipment, Furnishings Georgia Calhoun Mohawk Industries 30701 41,900
55 Trucking, Truck Leasing Arkansas Lowell J.B. Hunt Transport Services 72745 33,600
56 Metals North Carolina Charlotte Nucor 28211 32,700
57 Railroads Nebraska Omaha Union Pacific 68179 32,400
58 Automotive Retailing, Services Oregon Medford Lithia Motors 97501 30,200
59 Building Materials, Glass Texas Irving Builders FirstSource 75039 29,000
60 Mining, Crude-Oil Production Arizona Phoenix Freeport-McMoRan 85004 28,500
61 Utilities: Gas and Electric Georgia Atlanta Southern 30308 28,500
62 Wholesalers: Electronics and Office Equipment California Irvine Ingram Micro 92612 26,100
63 Publishing, Printing New York New York News Corp. 10036 23,900
64 Pipelines Texas Dallas Energy Transfer 75225 16,200
65 Insurance: Life, Health (Mutual) New York New York TIAA 10017 15,600
66 Homebuilders Texas Arlington D.R. Horton 76011 14,800
In [89]:
# Join the Dataframe 'gdfusact' with 'dfinsmaxempco' for the Biggest Employer Company in each Industry visualized by City
dfinsmaxempco = dfinsmaxempco.head(10)
gdfusactinsmaxempco = gdfusact.merge(dfinsmaxempco, how = 'inner', on = ['Zip Code'])
gdfusactinsmaxempco = gdfusactinsmaxempco.sort_values('Employees', ascending=False).reset_index(drop=True)

# Join the Dataframe 'gdfsts' with 'dfinsmaxempco' for the Biggest Employer Company in each Industry visualized by State
gdfstsinmaxempco = gdfsts.merge(dfinsmaxempco, how = 'inner', on = ['State'])
gdfstsinmaxempco = gdfstsinmaxempco.sort_values('Employees', ascending=False).reset_index(drop=True)
In [90]:
# Draw the Map visualizing the Biggest Employer Company in each Industry by State and City
minsmaxempco = gdfstsinmaxempco.explore(column='Employees', name='The Biggest Employer in each Industry visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactinsmaxempco.explore(m=minsmaxempco, column='Employees', name='The Biggest Employer in each Industry visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(minsmaxempco)
minsmaxempco
Out[90]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [91]:
# Check the Smallest Employer Company in each Industry
dfinsminempco = df.head(1)

for ins in inslist[0:]:
    dfin = df.where(df['Industry'] == ins[0]).dropna()
    mninsminemp = dfin['Employees'].min()
    dfinminempco = dfin.where(dfin['Employees'] == mninsminemp).dropna()
    dfinsminempco = pd.concat([dfinsminempco, dfinminempco], ignore_index=True)
    
dfinsminempco = dfinsminempco.drop(0)
dfinsminempco = dfinsminempco[['Industry','State','City','Company','Zip Code','Employees']].sort_values(by='Employees', ascending=False).reset_index(drop=True)
dfinsminempco
Out[91]:
Industry State City Company Zip Code Employees
0 Mail, Package and Freight Delivery Georgia Atlanta UPS 30328 372,200
1 Scientific, Photographic and Control Equipment Massachusetts Waltham Thermo Fisher Scientific 02451 125,000
2 Advertising, Marketing New York New York Interpublic 10022 53,300
3 Health Care: Medical Facilities Tennessee Franklin Community Health Systems 37067 52,500
4 Waste Management Arizona Phoenix Republic Services 85054 42,000
5 Hotels, Casinos, Resorts Nevada Las Vegas Las Vegas Sands 89113 40,100
6 Health Care: Pharmacy and Other Services Kentucky Louisville BrightSpring Health Services 40222 37,000
7 Food & Drug Stores Arizona Phoenix Sprouts Farmers Market 85054 35,000
8 Oil and Gas Equipment, Services Texas Houston NOV 77042 34,000
9 Trucking, Truck Leasing Arkansas Lowell J.B. Hunt Transport Services 72745 33,600
10 General Merchandisers Massachusetts Marlborough BJ's Wholesale Club 01752 33,000
11 Food Services Kentucky Louisville Yum Brands 40213 31,700
12 Specialty Retailers: Apparel New York New York Foot Locker 10001 30,200
13 Electronics, Electrical Equip. Wisconsin Milwaukee Rockwell Automation 53204 27,000
14 Engineering & Construction Texas Irving Fluor 75039 26,900
15 Diversified Outsourcing Services Wisconsin Milwaukee Manpower 53212 26,700
16 Publishing, Printing New York New York News Corp. 10036 23,900
17 Wholesalers: Health Care Virginia Glen Allen Owens & Minor 23060 23,200
18 Industrial Machinery District of Columbia Washington Xylem 20003 23,000
19 Motor Vehicles & Parts Indiana Elkhart THOR Industries 46514 22,300
20 Household and Personal Products New Jersey Summit Kenvue 07901 22,000
21 Computer Software California Pleasanton Workday 94588 20,500
22 Airlines New York Long Island City JetBlue Airways 11101 19,800
23 Railroads Georgia Atlanta Norfolk Southern 30308 19,600
24 Construction and Farm Machinery Wisconsin Oshkosh Oshkosh 54902 18,500
25 Home Equipment, Furnishings Michigan Livonia Masco 48152 18,000
26 Commercial Banks Ohio Cleveland KeyCorp 44114 16,800
27 Aerospace & Defense Ohio Cleveland TransDigm 44115 16,600
28 Medical Products and Equipment California Sunnyvale Intuitive Surgical 94086 15,600
29 Wholesalers: Electronics and Office Equipment Arizona Phoenix Avnet 85034 15,500
30 Packaging, Containers Illinois Lake Forest Packaging Corp. of America 60045 15,400
31 Network and Other Communications Equipment California Santa Clara Palo Alto Networks 95054 15,300
32 Semiconductors and Other Electronic Components California Milpitas KLA 95035 15,100
33 Apparel California Manhattan Beach Skechers U.S.A. 90266 15,100
34 Wholesalers: Food and Grocery Michigan Byron Center SpartanNash 49315 15,000
35 Information Technology Services Arizona Chandler Insight Enterprises 85286 14,300
36 Transportation and Logistics Minnesota Eden Prairie C.H. Robinson Worldwide 55347 13,800
37 Metals Indiana Fort Wayne Steel Dynamics 46804 13,000
38 Chemicals Texas Irving Celanese 75039 12,200
39 Building Materials, Glass Alabama Birmingham Vulcan Materials 35242 12,000
40 Specialty Retailers: Other Arkansas El Dorado Murphy USA 71730 11,600
41 Financial Data Services California Oakland Block 94612 11,400
42 Telecommunications New York Long Island City Altice USA 11101 10,900
43 Food Consumer Products Minnesota Arden Hills Land O'Lakes 55126 9,000
44 Food Consumer Products Ohio Orrville J.M. Smucker 44667 9,000
45 Automotive Retailing, Services Texas New Braunfels Rush Enterprises 78130 7,900
46 Internet Services and Retailing California San Francisco Airbnb 94103 7,300
47 Utilities: Gas and Electric Pennsylvania Allentown PPL 18101 6,700
48 Insurance: Property and Casualty (Mutual) Pennsylvania Erie Erie Insurance 16530 6,700
49 Tobacco Virginia Richmond Altria 23230 6,200
50 Pharmaceuticals Massachusetts Boston Vertex Pharmaceuticals 02210 6,100
51 Beverages California Corona Monster Beverage 92879 6,000
52 Computers, Office Equipment California San Jose Super Micro Computer 95131 5,700
53 Insurance: Property and Casualty (Stock) Ohio Fairfield Cincinnati Financial 45014 5,600
54 Entertainment New York New York Sirius XM 10020 5,500
55 Diversified Financials New York New York StoneX 10169 4,500
56 Insurance: Life, Health (Stock) Missouri Chesterfield Reinsurance of America 63017 4,100
57 Energy Massachusetts Waltham Global Partners 02453 3,800
58 Securities Connecticut Greenwich Interactive Brokers 06830 3,000
59 Homebuilders Arizona Scottsdale Taylor Morrison Home 85251 3,000
60 Insurance: Life, Health (Mutual) Ohio Cincinnati Western & Southern Financial 45202 2,700
61 Health Care: Insurance and Managed Care New York New York Oscar Health 10013 2,400
62 Food Production Ohio Maumee Andersons 43537 2,300
63 Petroleum Refining Texas Houston Par Pacific 77024 1,800
64 Pipelines Texas Houston Cheniere Energy 77002 1,700
65 Mining, Crude-Oil Production Colorado Denver Ovintiv 80202 1,600
66 Real Estate Ohio Toledo Welltower 43615 700
67 Wholesalers: Diversified California El Segundo A-Mark Precious Metals 90245 500
In [ ]:
 
In [92]:
# Join the Dataframe 'gdfusact' with 'dfinsminempco' for the Smallest Employer Company in each Industry visualized by City
dfinsminempco = dfinsminempco.head(10)
gdfusactinsminempco = gdfusact.merge(dfinsminempco, how = 'inner', on = ['Zip Code'])
gdfusactinsminempco = gdfusactinsminempco.sort_values('Employees', ascending=False).reset_index(drop=True)

# Join the Dataframe 'gdfsts' with 'dfinsminempco' for the Smallest Employer Company in each Industry visualized by State
gdfstsinminempco = gdfsts.merge(dfinsminempco, how = 'inner', on = ['State'])
gdfstsinminempco = gdfstsinminempco.sort_values('Employees', ascending=False).reset_index(drop=True)
In [93]:
minsminempco = gdfstsinminempco.explore(column='Employees', name='The Smallest Employer Company in each Industry visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactinsminempco.explore(m=minsminempco, column='Employees', name='The Smallest Employer Company in each Industry visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(minsminempco)
minsminempco
Out[93]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [94]:
# Check the Biggest Revenue Industry in each State.
# We use PARTITION BY-like feature to grouping but not making any new Index.
dummy = {'Revenue (rounded)': [1],
           'State': ['Dummy'],
            'Industry': ['Dummy']}
dfstmaxrevin = pd.DataFrame(dummy)
dfst = None

for st in stslist[0:]:
    dfst = df.where(df['State'] == st[0]).dropna()
    #print(dfst)
    dfstmaxrevin = pd.concat([dfstmaxrevin, dfst.groupby(['State','Industry'], as_index=False).sum("Revenue (rounded)").sort_values(by=['Revenue (rounded)'], ascending=False)[['State','Industry','Revenue (rounded)']].head(1)])
    
dfstmaxrevin = dfstmaxrevin.iloc[1:]
dfstmaxrevin = dfstmaxrevin[['State','Industry','Revenue (rounded)']].sort_values(by=['Revenue (rounded)'], ascending=False).reset_index(drop=True)
dfstmaxrevin
Out[94]:
State Industry Revenue (rounded)
0 Texas Petroleum Refining 858,500,000,000
1 New York Commercial Banks 737,300,000,000
2 Washington Internet Services and Retailing 682,000,000,000
3 Arkansas General Merchandisers 681,000,000,000
4 California Internet Services and Retailing 590,600,000,000
5 Michigan Motor Vehicles & Parts 420,200,000,000
6 Minnesota Health Care: Insurance and Managed Care 400,300,000,000
7 Rhode Island Health Care: Pharmacy and Other Services 372,800,000,000
8 Nebraska Insurance: Property and Casualty (Stock) 371,400,000,000
9 Pennsylvania Wholesalers: Health Care 294,000,000,000
10 Virginia Aerospace & Defense 247,400,000,000
11 Connecticut Health Care: Pharmacy and Other Services 247,100,000,000
12 North Carolina Commercial Banks 233,000,000,000
13 Ohio Wholesalers: Health Care 226,800,000,000
14 New Jersey Pharmaceuticals 210,600,000,000
15 Indiana Health Care: Insurance and Managed Care 177,000,000,000
16 Missouri Health Care: Insurance and Managed Care 163,100,000,000
17 Georgia Specialty Retailers: Other 159,500,000,000
18 District of Columbia Diversified Financials 152,700,000,000
19 Illinois Food & Drug Stores 147,700,000,000
20 Kentucky Health Care: Insurance and Managed Care 117,800,000,000
21 Tennessee Mail, Package and Freight Delivery 87,700,000,000
22 Idaho Food & Drug Stores 79,200,000,000
23 Maryland Aerospace & Defense 71,000,000,000
24 Florida Food & Drug Stores 60,200,000,000
25 Massachusetts Specialty Retailers: Apparel 56,400,000,000
26 Oregon Apparel 51,400,000,000
27 Wisconsin Insurance: Life, Health (Mutual) 41,400,000,000
28 Nevada Hotels, Casinos, Resorts 39,800,000,000
29 Oklahoma Pipelines 32,200,000,000
30 Colorado Mining, Crude-Oil Production 27,900,000,000
31 Arizona Mining, Crude-Oil Production 25,500,000,000
32 Iowa Insurance: Life, Health (Stock) 16,100,000,000
33 Louisiana Telecommunications 13,100,000,000
34 Delaware Chemicals 12,400,000,000
35 Alabama Commercial Banks 9,400,000,000
36 Kansas Food Production 9,100,000,000
In [ ]:
# Conclusion: the Biggest Revenue Industry is Petroleum Refining
In [95]:
dfstmaxrevin = dfstmaxrevin.head(10)
dfstmaxrevin = dfstmaxrevin.merge(df[['State','Company','Industry','Zip Code']], how = 'inner', on = ['State','Industry'])
dfstmaxrevin = dfstmaxrevin[['State','Industry','Company','Zip Code','Revenue (rounded)']].sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
dfstmaxrevin
Out[95]:
State Industry Company Zip Code Revenue (rounded)
0 Texas Petroleum Refining Exxon Mobil 77389 858,500,000,000
1 Texas Petroleum Refining Chevron 77002 858,500,000,000
2 Texas Petroleum Refining Phillips 66 77042 858,500,000,000
3 Texas Petroleum Refining Valero Energy 78249 858,500,000,000
4 Texas Petroleum Refining HF Sinclair 75219 858,500,000,000
5 Texas Petroleum Refining Par Pacific 77024 858,500,000,000
6 New York Commercial Banks JPMorgan Chase 10017 737,300,000,000
7 New York Commercial Banks Citi 10013 737,300,000,000
8 New York Commercial Banks Goldman Sachs 10282 737,300,000,000
9 New York Commercial Banks Morgan Stanley 10036 737,300,000,000
10 New York Commercial Banks Bank of New York 10286 737,300,000,000
11 New York Commercial Banks M&T Bank 14203 737,300,000,000
12 Washington Internet Services and Retailing Amazon 98109 682,000,000,000
13 Washington Internet Services and Retailing Coupang 98101 682,000,000,000
14 Washington Internet Services and Retailing Expedia 98119 682,000,000,000
15 Arkansas General Merchandisers Walmart 72712 681,000,000,000
16 California Internet Services and Retailing Alphabet 94043 590,600,000,000
17 California Internet Services and Retailing Meta 94025 590,600,000,000
18 California Internet Services and Retailing Uber 94158 590,600,000,000
19 California Internet Services and Retailing Airbnb 94103 590,600,000,000
20 California Internet Services and Retailing DoorDash 94107 590,600,000,000
21 California Internet Services and Retailing Ebay 95125 590,600,000,000
22 Michigan Motor Vehicles & Parts General Motors 48265 420,200,000,000
23 Michigan Motor Vehicles & Parts Ford Motor 48126 420,200,000,000
24 Michigan Motor Vehicles & Parts Lear 48033 420,200,000,000
25 Michigan Motor Vehicles & Parts BorgWarner 48326 420,200,000,000
26 Michigan Motor Vehicles & Parts Autoliv 48326 420,200,000,000
27 Minnesota Health Care: Insurance and Managed Care UnitedHealth 55344 400,300,000,000
28 Rhode Island Health Care: Pharmacy and Other Services CVS Health 02895 372,800,000,000
29 Nebraska Insurance: Property and Casualty (Stock) Berkshire Hathaway 68131 371,400,000,000
30 Pennsylvania Wholesalers: Health Care Cencora 19428 294,000,000,000
In [96]:
gdfstsmaxrevin = gdfsts.merge(dfstmaxrevin, how = 'inner', on = ['State'])
gdfusactmaxrevin = gdfusact.merge(dfstmaxrevin, how = 'inner', on = ['Zip Code'])
gdfusactmaxrevin
mstmaxrevin = gdfstsmaxrevin.explore(column='Revenue (rounded)', name='The Biggest Revenue Industry in each State visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactmaxrevin.explore(m=mstmaxrevin, column='Revenue (rounded)', name='The Biggest Revenue Company in each State visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mstmaxrevin)
mstmaxrevin
Out[96]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [99]:
# Check the Smallest Revenue Industry in each State.
# We use PARTITION BY-like feature to grouping but not making any new Index.
dummy = {'Revenue (rounded)': [1],
           'State': ['Dummy'],
            'Industry': ['Dummy']}
dfstminrevin = pd.DataFrame(dummy)
dfst = None

for st in stslist[0:]:
    dfst = df.where(df['State'] == st[0]).dropna()
    dfstminrevin = pd.concat([dfstminrevin, dfst.groupby(['State','Industry'], as_index=False).sum("Revenue (rounded)").sort_values(by=['Revenue (rounded)'], ascending=True)[['State','Industry','Revenue (rounded)']].head(1)])
dfstminrevin = dfstminrevin.iloc[1:]
dfstminrevin[['State','Industry','Revenue (rounded)']].sort_values(by=['Revenue (rounded)'], ascending=False).reset_index(drop=True)
Out[99]:
State Industry Revenue (rounded)
0 Nevada Hotels, Casinos, Resorts 39,800,000,000
1 Oregon Automotive Retailing, Services 36,600,000,000
2 Idaho Semiconductors and Other Electronic Components 25,100,000,000
3 Maryland Energy 23,600,000,000
4 Oklahoma Mining, Crude-Oil Production 15,900,000,000
5 Iowa Specialty Retailers: Other 14,900,000,000
6 Nebraska Insurance: Life, Health (Mutual) 14,600,000,000
7 North Carolina Automotive Retailing, Services 14,200,000,000
8 Delaware Chemicals 12,400,000,000
9 Arkansas Trucking, Truck Leasing 12,100,000,000
10 Louisiana Utilities: Gas and Electric 11,900,000,000
11 Virginia Homebuilders 10,700,000,000
12 Washington Specialty Retailers: Apparel 10,600,000,000
13 Rhode Island Insurance: Property and Casualty (Stock) 10,400,000,000
14 Colorado Internet Services and Retailing 10,000,000,000
15 New Jersey Food Consumer Products 9,600,000,000
16 Tennessee Chemicals 9,400,000,000
17 Connecticut Securities 9,400,000,000
18 Massachusetts Semiconductors and Other Electronic Components 9,400,000,000
19 Kansas Food Production 9,100,000,000
20 Georgia Packaging, Containers 8,800,000,000
21 District of Columbia Industrial Machinery 8,600,000,000
22 Illinois Packaging, Containers 8,400,000,000
23 Wisconsin Electronics, Electrical Equip. 8,300,000,000
24 Ohio Electronics, Electrical Equip. 8,000,000,000
25 New York Specialty Retailers: Apparel 8,000,000,000
26 Missouri Food Consumer Products 7,900,000,000
27 Michigan Home Equipment, Furnishings 7,800,000,000
28 Indiana Medical Products and Equipment 7,700,000,000
29 Texas Information Technology Services 7,700,000,000
30 Arizona Semiconductors and Other Electronic Components 7,600,000,000
31 Florida Wholesalers: Diversified 7,600,000,000
32 Kentucky Food Services 7,500,000,000
33 California Beverages 7,500,000,000
34 Minnesota Wholesalers: Diversified 7,500,000,000
35 Pennsylvania Aerospace & Defense 7,400,000,000
36 Alabama Building Materials, Glass 7,400,000,000
In [100]:
dfstminrevin = dfstminrevin.merge(df[['State','Company','Industry','Zip Code']], how = 'inner', on = ['State','Industry'])
dfstminrevin = dfstminrevin[['State','Industry','Company','Zip Code','Revenue (rounded)']].sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
dfstminrevin
Out[100]:
State Industry Company Zip Code Revenue (rounded)
0 Nevada Hotels, Casinos, Resorts MGM Resorts International 89109 39,800,000,000
1 Nevada Hotels, Casinos, Resorts Caesars Entertainment 89501 39,800,000,000
2 Nevada Hotels, Casinos, Resorts Las Vegas Sands 89113 39,800,000,000
3 Oregon Automotive Retailing, Services Lithia Motors 97501 36,600,000,000
4 Idaho Semiconductors and Other Electronic Components Micron Technology 83716 25,100,000,000
5 Maryland Energy Constellation Energy 21231 23,600,000,000
6 Oklahoma Mining, Crude-Oil Production Devon Energy 73102 15,900,000,000
7 Iowa Specialty Retailers: Other Casey's General Stores 50021 14,900,000,000
8 Nebraska Insurance: Life, Health (Mutual) Mutual of Omaha Insurance 68175 14,600,000,000
9 North Carolina Automotive Retailing, Services Sonic Automotive 28211 14,200,000,000
10 Delaware Chemicals DuPont 19805 12,400,000,000
11 Arkansas Trucking, Truck Leasing J.B. Hunt Transport Services 72745 12,100,000,000
12 Louisiana Utilities: Gas and Electric Entergy 70113 11,900,000,000
13 Virginia Homebuilders NVR 20190 10,700,000,000
14 Washington Specialty Retailers: Apparel Lululemon athletica 98390 10,600,000,000
15 Rhode Island Insurance: Property and Casualty (Stock) FM 02919 10,400,000,000
16 Colorado Internet Services and Retailing QVC 80112 10,000,000,000
17 New Jersey Food Consumer Products Campbell's 08103 9,600,000,000
18 Tennessee Chemicals Eastman Chemical 37660 9,400,000,000
19 Connecticut Securities Interactive Brokers 06830 9,400,000,000
20 Massachusetts Semiconductors and Other Electronic Components Analog Devices 01887 9,400,000,000
21 Kansas Food Production Seaboard 66202 9,100,000,000
22 Georgia Packaging, Containers Graphic Packaging 30328 8,800,000,000
23 District of Columbia Industrial Machinery Xylem 20003 8,600,000,000
24 Illinois Packaging, Containers Packaging Corp. of America 60045 8,400,000,000
25 Wisconsin Electronics, Electrical Equip. Rockwell Automation 53204 8,300,000,000
26 New York Specialty Retailers: Apparel Foot Locker 10001 8,000,000,000
27 Ohio Electronics, Electrical Equip. Vertiv s 43082 8,000,000,000
28 Missouri Food Consumer Products Post s 63144 7,900,000,000
29 Michigan Home Equipment, Furnishings Masco 48152 7,800,000,000
30 Indiana Medical Products and Equipment Zimmer Biomet s 46580 7,700,000,000
31 Texas Information Technology Services KBR 77002 7,700,000,000
32 Arizona Semiconductors and Other Electronic Components Microchip Technology 85224 7,600,000,000
33 Florida Wholesalers: Diversified Watsco 33133 7,600,000,000
34 California Beverages Monster Beverage 92879 7,500,000,000
35 Minnesota Wholesalers: Diversified Fastenal 55987 7,500,000,000
36 Kentucky Food Services Yum Brands 40213 7,500,000,000
37 Pennsylvania Aerospace & Defense Howmet Aerospace 15212 7,400,000,000
38 Alabama Building Materials, Glass Vulcan Materials 35242 7,400,000,000
In [101]:
gdfstsminrevin = gdfsts.merge(dfstminrevin, how = 'inner', on = ['State'])
gdfusactminrevin = gdfusact.merge(dfstminrevin, how = 'inner', on = ['Zip Code']).sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
gdfusactminrevin
Out[101]:
Zip Code Latitude Longitude Population geometry State Industry Company Revenue (rounded)
0 89501 40 -120 3,641 POINT (-119.81262 39.52602) Nevada Hotels, Casinos, Resorts Caesars Entertainment 39,800,000,000
1 89113 36 -115 37,313 POINT (-115.26236 36.06017) Nevada Hotels, Casinos, Resorts Las Vegas Sands 39,800,000,000
2 89109 36 -115 6,924 POINT (-115.16327 36.12603) Nevada Hotels, Casinos, Resorts MGM Resorts International 39,800,000,000
3 97501 42 -123 45,008 POINT (-122.89459 42.2856) Oregon Automotive Retailing, Services Lithia Motors 36,600,000,000
4 83716 44 -116 21,091 POINT (-115.6548 43.67271) Idaho Semiconductors and Other Electronic Components Micron Technology 25,100,000,000
5 21231 39 -77 14,556 POINT (-76.592 39.28775) Maryland Energy Constellation Energy 23,600,000,000
6 73102 35 -98 3,590 POINT (-97.5191 35.47065) Oklahoma Mining, Crude-Oil Production Devon Energy 15,900,000,000
7 50021 42 -94 29,718 POINT (-93.56838 41.7207) Iowa Specialty Retailers: Other Casey's General Stores 14,900,000,000
8 68175 41 -96 0 POINT (-95.96584 41.26502) Nebraska Insurance: Life, Health (Mutual) Mutual of Omaha Insurance 14,600,000,000
9 28211 35 -81 32,637 POINT (-80.79604 35.16816) North Carolina Automotive Retailing, Services Sonic Automotive 14,200,000,000
10 19805 40 -76 40,315 POINT (-75.59373 39.74523) Delaware Chemicals DuPont 12,400,000,000
11 72745 36 -94 14,521 POINT (-94.10046 36.2477) Arkansas Trucking, Truck Leasing J.B. Hunt Transport Services 12,100,000,000
12 70113 30 -90 9,888 POINT (-90.08382 29.9422) Louisiana Utilities: Gas and Electric Entergy 11,900,000,000
13 20190 39 -77 22,092 POINT (-77.33806 38.95968) Virginia Homebuilders NVR 10,700,000,000
14 98390 47 -122 11,497 POINT (-122.22894 47.21195) Washington Specialty Retailers: Apparel Lululemon athletica 10,600,000,000
15 02919 42 -72 29,473 POINT (-71.52002 41.82733) Rhode Island Insurance: Property and Casualty (Stock) FM 10,400,000,000
16 80112 40 -105 36,687 POINT (-104.85854 39.57288) Colorado Internet Services and Retailing QVC 10,000,000,000
17 08103 40 -75 13,137 POINT (-75.11275 39.93533) New Jersey Food Consumer Products Campbell's 9,600,000,000
18 06830 41 -74 24,919 POINT (-73.624 41.048) Connecticut Securities Interactive Brokers 9,400,000,000
19 01887 43 -71 23,195 POINT (-71.16541 42.56091) Massachusetts Semiconductors and Other Electronic Components Analog Devices 9,400,000,000
20 37660 37 -83 40,114 POINT (-82.57339 36.52938) Tennessee Chemicals Eastman Chemical 9,400,000,000
21 66202 39 -95 17,321 POINT (-94.66909 39.02392) Kansas Food Production Seaboard 9,100,000,000
22 30328 34 -84 38,821 POINT (-84.38617 33.93194) Georgia Packaging, Containers Graphic Packaging 8,800,000,000
23 20003 39 -77 36,194 POINT (-76.99033 38.88193) District of Columbia Industrial Machinery Xylem 8,600,000,000
24 60045 42 -88 20,957 POINT (-87.87006 42.23807) Illinois Packaging, Containers Packaging Corp. of America 8,400,000,000
25 53204 43 -88 40,008 POINT (-87.92552 43.01806) Wisconsin Electronics, Electrical Equip. Rockwell Automation 8,300,000,000
26 43082 40 -83 33,799 POINT (-82.88437 40.15537) Ohio Electronics, Electrical Equip. Vertiv s 8,000,000,000
27 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York Specialty Retailers: Apparel Foot Locker 8,000,000,000
28 63144 39 -90 9,580 POINT (-90.3482 38.61943) Missouri Food Consumer Products Post s 7,900,000,000
29 48152 42 -83 30,394 POINT (-83.37433 42.42597) Michigan Home Equipment, Furnishings Masco 7,800,000,000
30 46580 41 -86 21,812 POINT (-85.87212 41.20884) Indiana Medical Products and Equipment Zimmer Biomet s 7,700,000,000
31 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas Information Technology Services KBR 7,700,000,000
32 85224 33 -112 48,304 POINT (-111.87616 33.32351) Arizona Semiconductors and Other Electronic Components Microchip Technology 7,600,000,000
33 33133 26 -80 34,651 POINT (-80.24327 25.72983) Florida Wholesalers: Diversified Watsco 7,600,000,000
34 55987 44 -92 33,911 POINT (-91.63143 43.98469) Minnesota Wholesalers: Diversified Fastenal 7,500,000,000
35 92879 34 -118 48,756 POINT (-117.5357 33.87979) California Beverages Monster Beverage 7,500,000,000
36 40213 38 -86 15,805 POINT (-85.71571 38.177) Kentucky Food Services Yum Brands 7,500,000,000
37 15212 40 -80 27,600 POINT (-80.00844 40.47106) Pennsylvania Aerospace & Defense Howmet Aerospace 7,400,000,000
38 35242 33 -87 56,956 POINT (-86.67073 33.42371) Alabama Building Materials, Glass Vulcan Materials 7,400,000,000
In [102]:
mstminrevin = gdfstsminrevin.explore(column='Revenue (rounded)', name='The Smallest Revenue Industry in each State visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactminrevin.explore(m=mstminrevin, column='Revenue (rounded)', name='The Smallest Revenue Company in each State visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mstminrevin)
mstminrevin
Out[102]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [103]:
# Check the Biggest Employer Industry in each State.
# We use PARTITION BY-like feature to grouping but not making any new Index.
dummy = {'Employees': [1],
           'State': ['Dummy'],
            'Industry': ['Dummy']}
dfstmaxempin = pd.DataFrame(dummy)

for st in stslist[0:]:
    dfst = df.where(df['State'] == st[0]).dropna()
    dfstmaxempin = pd.concat([dfstmaxempin, dfst.groupby(['State','Industry'], as_index=False).sum('Employees').sort_values(by=['Employees'], 
                        ascending=False)[['State','Industry','Employees']].head(1)])
    
dfstmaxempin = dfstmaxempin.iloc[1:]
dfstmaxempin[['State','Industry','Employees']].sort_values(by=['Employees'], ascending=False).reset_index(drop=True)
Out[103]:
State Industry Employees
0 Arkansas General Merchandisers 2,100,000
1 Washington Internet Services and Retailing 1,667,500
2 New York Commercial Banks 746,000
3 Virginia Aerospace & Defense 616,000
4 Michigan Motor Vehicles & Parts 607,300
5 Georgia Specialty Retailers: Other 470,100
6 California Information Technology Services 450,000
7 Minnesota General Merchandisers 440,000
8 Tennessee Mail, Package and Freight Delivery 422,100
9 Ohio Food & Drug Stores 409,000
10 Nebraska Insurance: Property and Casualty (Stock) 392,400
11 Massachusetts Specialty Retailers: Apparel 364,000
12 New Jersey Information Technology Services 336,800
13 North Carolina Commercial Banks 268,100
14 Pennsylvania Diversified Outsourcing Services 266,700
15 Rhode Island Health Care: Pharmacy and Other Services 259,500
16 Florida Food & Drug Stores 255,000
17 Illinois Food & Drug Stores 252,500
18 Texas Food Services 245,500
19 Idaho Food & Drug Stores 196,600
20 Connecticut Transportation and Logistics 168,000
21 Nevada Hotels, Casinos, Resorts 159,100
22 Maryland Hotels, Casinos, Resorts 155,000
23 Indiana Health Care: Insurance and Managed Care 103,700
24 Missouri Specialty Retailers: Other 85,600
25 Oregon Apparel 79,400
26 Colorado Health Care: Medical Facilities 76,000
27 Kentucky Health Care: Insurance and Managed Care 65,700
28 District of Columbia Medical Products and Equipment 62,000
29 Wisconsin General Merchandisers 60,000
30 Arizona Waste Management 42,000
31 Iowa Specialty Retailers: Other 33,100
32 Louisiana Telecommunications 25,000
33 Delaware Chemicals 24,000
34 Alabama Commercial Banks 19,600
35 Kansas Food Production 14,000
36 Oklahoma Pipelines 11,000
In [ ]:
# Conclusion: the Biggest Employer Industry is General Merchandisers.
In [104]:
dfstmaxempin = dfstmaxempin.merge(df[['State','Company','Industry','Zip Code']], how = 'inner', on = ['State','Industry'])
dfstmaxempin[['State','Industry','Company','Zip Code','Employees']].sort_values('Employees', ascending=False).reset_index(drop=True)
Out[104]:
State Industry Company Zip Code Employees
0 Arkansas General Merchandisers Walmart 72712 2,100,000
1 Washington Internet Services and Retailing Amazon 98109 1,667,500
2 Washington Internet Services and Retailing Coupang 98101 1,667,500
3 Washington Internet Services and Retailing Expedia 98119 1,667,500
4 New York Commercial Banks M&T Bank 14203 746,000
5 New York Commercial Banks Bank of New York 10286 746,000
6 New York Commercial Banks Morgan Stanley 10036 746,000
7 New York Commercial Banks Goldman Sachs 10282 746,000
8 New York Commercial Banks Citi 10013 746,000
9 New York Commercial Banks JPMorgan Chase 10017 746,000
10 Virginia Aerospace & Defense RTX 22209 616,000
11 Virginia Aerospace & Defense Boeing 22202 616,000
12 Virginia Aerospace & Defense General Dynamics 20190 616,000
13 Virginia Aerospace & Defense Northrop Grumman 22042 616,000
14 Virginia Aerospace & Defense Huntington Ingalls Industries 23607 616,000
15 Michigan Motor Vehicles & Parts General Motors 48265 607,300
16 Michigan Motor Vehicles & Parts Autoliv 48326 607,300
17 Michigan Motor Vehicles & Parts BorgWarner 48326 607,300
18 Michigan Motor Vehicles & Parts Lear 48033 607,300
19 Michigan Motor Vehicles & Parts Ford Motor 48126 607,300
20 Georgia Specialty Retailers: Other Home Depot 30339 470,100
21 California Information Technology Services Concentrix 94560 450,000
22 Minnesota General Merchandisers Target 55403 440,000
23 Tennessee Mail, Package and Freight Delivery FedEx 38120 422,100
24 Ohio Food & Drug Stores Kroger 45202 409,000
25 Nebraska Insurance: Property and Casualty (Stock) Berkshire Hathaway 68131 392,400
26 Massachusetts Specialty Retailers: Apparel TJX 01701 364,000
27 New Jersey Information Technology Services Cognizant Technology 07666 336,800
28 North Carolina Commercial Banks Truist Financial 28202 268,100
29 North Carolina Commercial Banks First Citizens BancShares 27609 268,100
30 North Carolina Commercial Banks Bank of America 28255 268,100
31 Pennsylvania Diversified Outsourcing Services Aramark 19103 266,700
32 Rhode Island Health Care: Pharmacy and Other Services CVS Health 02895 259,500
33 Florida Food & Drug Stores Publix Super Markets 33811 255,000
34 Illinois Food & Drug Stores Walgreens 60015 252,500
35 Texas Food Services Yum China s 75074 245,500
36 Idaho Food & Drug Stores Albertsons 83706 196,600
37 Connecticut Transportation and Logistics XPO 06831 168,000
38 Connecticut Transportation and Logistics GXO Logistics 06831 168,000
39 Nevada Hotels, Casinos, Resorts Caesars Entertainment 89501 159,100
40 Nevada Hotels, Casinos, Resorts Las Vegas Sands 89113 159,100
41 Nevada Hotels, Casinos, Resorts MGM Resorts International 89109 159,100
42 Maryland Hotels, Casinos, Resorts Marriott International 20814 155,000
43 Indiana Health Care: Insurance and Managed Care Elevance Health 46204 103,700
44 Missouri Specialty Retailers: Other O'Reilly Automotive 65802 85,600
45 Oregon Apparel Nike 97005 79,400
46 Colorado Health Care: Medical Facilities DaVita 80202 76,000
47 Kentucky Health Care: Insurance and Managed Care Humana 40202 65,700
48 District of Columbia Medical Products and Equipment Danaher 20037 62,000
49 Wisconsin General Merchandisers Kohl's 53051 60,000
50 Arizona Waste Management Republic Services 85054 42,000
51 Iowa Specialty Retailers: Other Casey's General Stores 50021 33,100
52 Louisiana Telecommunications Lumen Technologies 71203 25,000
53 Delaware Chemicals DuPont 19805 24,000
54 Alabama Commercial Banks Regions Financial 35203 19,600
55 Kansas Food Production Seaboard 66202 14,000
56 Oklahoma Pipelines Williams 74172 11,000
57 Oklahoma Pipelines Oneok 74103 11,000
In [105]:
gdfstsmaxempin = gdfsts.merge(dfstmaxempin, how = 'inner', on = ['State'])
gdfusactmaxempin = gdfusact.merge(dfstmaxempin, how = 'inner', on = ['Zip Code']).sort_values('Employees', ascending=False).reset_index(drop=True)
gdfusactmaxempin
Out[105]:
Zip Code Latitude Longitude Population geometry Employees State Industry Company
0 72712 36 -94 38,072 POINT (-94.22196 36.39837) 2,100,000 Arkansas General Merchandisers Walmart
1 98119 48 -122 26,390 POINT (-122.36932 47.63943) 1,667,500 Washington Internet Services and Retailing Expedia
2 98109 48 -122 32,552 POINT (-122.34486 47.63128) 1,667,500 Washington Internet Services and Retailing Amazon
3 98101 48 -122 16,396 POINT (-122.33454 47.61119) 1,667,500 Washington Internet Services and Retailing Coupang
4 10282 41 -74 5,960 POINT (-74.01495 40.71655) 746,000 New York Commercial Banks Goldman Sachs
5 10286 41 -74 5,269 POINT (-74.01182 40.7052) 746,000 New York Commercial Banks Bank of New York
6 10013 41 -74 28,215 POINT (-74.00472 40.72001) 746,000 New York Commercial Banks Citi
7 10017 41 -74 14,985 POINT (-73.9726 40.75235) 746,000 New York Commercial Banks JPMorgan Chase
8 10036 41 -74 30,589 POINT (-73.99064 40.75976) 746,000 New York Commercial Banks Morgan Stanley
9 14203 43 -79 2,526 POINT (-78.86507 42.86244) 746,000 New York Commercial Banks M&T Bank
10 23607 37 -76 23,028 POINT (-76.42235 36.98753) 616,000 Virginia Aerospace & Defense Huntington Ingalls Industries
11 22042 39 -77 34,631 POINT (-77.19406 38.86463) 616,000 Virginia Aerospace & Defense Northrop Grumman
12 20190 39 -77 22,092 POINT (-77.33806 38.95968) 616,000 Virginia Aerospace & Defense General Dynamics
13 22209 39 -77 13,725 POINT (-77.07309 38.89413) 616,000 Virginia Aerospace & Defense RTX
14 22202 39 -77 27,352 POINT (-77.05175 38.8569) 616,000 Virginia Aerospace & Defense Boeing
15 48326 43 -83 24,488 POINT (-83.2531 42.67536) 607,300 Michigan Motor Vehicles & Parts Autoliv
16 48326 43 -83 24,488 POINT (-83.2531 42.67536) 607,300 Michigan Motor Vehicles & Parts BorgWarner
17 48126 42 -83 52,075 POINT (-83.18678 42.32999) 607,300 Michigan Motor Vehicles & Parts Ford Motor
18 48265 42 -83 4,503 POINT (-83.0456 42.3317) 607,300 Michigan Motor Vehicles & Parts General Motors
19 48033 42 -83 16,900 POINT (-83.28812 42.46478) 607,300 Michigan Motor Vehicles & Parts Lear
20 30339 34 -84 34,872 POINT (-84.46483 33.86786) 470,100 Georgia Specialty Retailers: Other Home Depot
21 94560 38 -122 47,145 POINT (-122.02523 37.50771) 450,000 California Information Technology Services Concentrix
22 55403 45 -93 17,354 POINT (-93.28588 44.97023) 440,000 Minnesota General Merchandisers Target
23 38120 35 -90 13,249 POINT (-89.85237 35.12344) 422,100 Tennessee Mail, Package and Freight Delivery FedEx
24 45202 39 -85 17,022 POINT (-84.50243 39.10885) 409,000 Ohio Food & Drug Stores Kroger
25 68131 41 -96 13,928 POINT (-95.96479 41.26435) 392,400 Nebraska Insurance: Property and Casualty (Stock) Berkshire Hathaway
26 01701 42 -71 32,270 POINT (-71.43796 42.32195) 364,000 Massachusetts Specialty Retailers: Apparel TJX
27 07666 41 -74 41,499 POINT (-74.01067 40.88998) 336,800 New Jersey Information Technology Services Cognizant Technology
28 28255 35 -81 0 POINT (-80.8434 35.2267) 268,100 North Carolina Commercial Banks Bank of America
29 28202 35 -81 16,855 POINT (-80.8447 35.22773) 268,100 North Carolina Commercial Banks Truist Financial
30 27609 36 -79 35,548 POINT (-78.63282 35.8437) 268,100 North Carolina Commercial Banks First Citizens BancShares
31 19103 40 -75 25,602 POINT (-75.17386 39.95303) 266,700 Pennsylvania Diversified Outsourcing Services Aramark
32 02895 42 -71 43,081 POINT (-71.49923 42.00103) 259,500 Rhode Island Health Care: Pharmacy and Other Services CVS Health
33 33811 28 -82 28,456 POINT (-82.01866 27.97933) 255,000 Florida Food & Drug Stores Publix Super Markets
34 60015 42 -88 27,720 POINT (-87.87486 42.17239) 252,500 Illinois Food & Drug Stores Walgreens
35 75074 33 -97 53,146 POINT (-96.67304 33.03298) 245,500 Texas Food Services Yum China s
36 83706 44 -116 36,183 POINT (-116.19427 43.59108) 196,600 Idaho Food & Drug Stores Albertsons
37 06831 41 -74 14,656 POINT (-73.66078 41.08782) 168,000 Connecticut Transportation and Logistics GXO Logistics
38 06831 41 -74 14,656 POINT (-73.66078 41.08782) 168,000 Connecticut Transportation and Logistics XPO
39 89501 40 -120 3,641 POINT (-119.81262 39.52602) 159,100 Nevada Hotels, Casinos, Resorts Caesars Entertainment
40 89113 36 -115 37,313 POINT (-115.26236 36.06017) 159,100 Nevada Hotels, Casinos, Resorts Las Vegas Sands
41 89109 36 -115 6,924 POINT (-115.16327 36.12603) 159,100 Nevada Hotels, Casinos, Resorts MGM Resorts International
42 20814 39 -77 30,822 POINT (-77.10295 39.00506) 155,000 Maryland Hotels, Casinos, Resorts Marriott International
43 46204 40 -86 11,022 POINT (-86.15703 39.77134) 103,700 Indiana Health Care: Insurance and Managed Care Elevance Health
44 65802 37 -93 46,005 POINT (-93.35167 37.21048) 85,600 Missouri Specialty Retailers: Other O'Reilly Automotive
45 97005 45 -123 27,812 POINT (-122.80397 45.49144) 79,400 Oregon Apparel Nike
46 80202 40 -105 18,233 POINT (-104.99768 39.75156) 76,000 Colorado Health Care: Medical Facilities DaVita
47 40202 38 -86 7,109 POINT (-85.75205 38.25288) 65,700 Kentucky Health Care: Insurance and Managed Care Humana
48 20037 39 -77 12,441 POINT (-77.0535 38.89213) 62,000 District of Columbia Medical Products and Equipment Danaher
49 53051 43 -88 39,000 POINT (-88.12348 43.14905) 60,000 Wisconsin General Merchandisers Kohl's
50 85054 34 -112 10,159 POINT (-111.94763 33.67515) 42,000 Arizona Waste Management Republic Services
51 50021 42 -94 29,718 POINT (-93.56838 41.7207) 33,100 Iowa Specialty Retailers: Other Casey's General Stores
52 71203 33 -92 38,770 POINT (-92.01351 32.58398) 25,000 Louisiana Telecommunications Lumen Technologies
53 19805 40 -76 40,315 POINT (-75.59373 39.74523) 24,000 Delaware Chemicals DuPont
54 35203 34 -87 3,301 POINT (-86.80999 33.51847) 19,600 Alabama Commercial Banks Regions Financial
55 66202 39 -95 17,321 POINT (-94.66909 39.02392) 14,000 Kansas Food Production Seaboard
56 74103 36 -96 2,419 POINT (-95.9957 36.15617) 11,000 Oklahoma Pipelines Oneok
57 74172 36 -96 0 POINT (-95.9905 36.1544) 11,000 Oklahoma Pipelines Williams
In [106]:
mstmaxempin = gdfstsmaxempin.explore(column='Employees', name='The Biggest Employer Industry in each State visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactmaxempin.explore(m=mstmaxempin, column='Employees', name='The Biggest Employer Industry in each State visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mstmaxempin)
mstmaxempin
Out[106]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [107]:
# Check the Smallest Employer Industry in each State.
# We use PARTITION BY-like feature to grouping but not making any new Index.
dummy = {'Employees': [1],
           'State': ['Dummy'],
            'Industry': ['Dummy']}
dfstminempin = pd.DataFrame(dummy)

for st in stslist[0:]:
    dfst = df.where(df['State'] == st[0]).dropna()
    dfstminempin = pd.concat([dfstminempin, dfst.groupby(['State','Industry'], as_index=False).sum('Employees').sort_values(by=['Employees'], 
                        ascending=True)[['State','Industry','Employees']].head(1)])

    
dfstminempin = dfstminempin.iloc[1:]
dfstminempin = dfstminempin.reset_index(drop=True)
dfstminempin[['State','Industry','Employees']].sort_values(by=['Employees'], ascending=False).reset_index(drop=True)
Out[107]:
State Industry Employees
0 Nevada Hotels, Casinos, Resorts 159,100
1 Idaho Semiconductors and Other Electronic Components 48,000
2 Kentucky Food Services 31,700
3 Oregon Automotive Retailing, Services 30,200
4 Delaware Chemicals 24,000
5 Iowa Insurance: Life, Health (Stock) 19,700
6 Washington Transportation and Logistics 18,900
7 Illinois Information Technology Services 15,100
8 Maryland Energy 14,200
9 Kansas Food Production 14,000
10 Colorado Telecommunications 13,700
11 Indiana Metals 13,000
12 Louisiana Utilities: Gas and Electric 12,300
13 Alabama Building Materials, Glass 12,000
14 Arkansas Specialty Retailers: Other 11,600
15 North Carolina Automotive Retailing, Services 10,800
16 District of Columbia Diversified Financials 8,200
17 Michigan Insurance: Property and Casualty (Mutual) 7,300
18 Wisconsin Utilities: Gas and Electric 7,000
19 Georgia Homebuilders 6,800
20 Nebraska Insurance: Life, Health (Mutual) 6,500
21 Virginia Tobacco 6,200
22 Rhode Island Insurance: Property and Casualty (Stock) 5,800
23 Texas Diversified Financials 5,200
24 Pennsylvania Homebuilders 4,900
25 Florida Energy 4,700
26 Massachusetts Real Estate 4,700
27 Missouri Insurance: Life, Health (Stock) 4,100
28 Minnesota Insurance: Life, Health (Mutual) 4,000
29 New Jersey Petroleum Refining 3,900
30 Connecticut Securities 3,000
31 Arizona Homebuilders 3,000
32 Oklahoma Mining, Crude-Oil Production 2,300
33 Tennessee Petroleum Refining 2,000
34 New York Mining, Crude-Oil Production 1,800
35 Ohio Real Estate 700
36 California Wholesalers: Diversified 500
In [108]:
dfstminempin = dfstminempin.merge(df[['State','Company','Industry','Zip Code']], how = 'inner', on = ['State','Industry'])
dfstminempin[['State','Industry','Company','Zip Code','Employees']].sort_values('Employees', ascending=False).reset_index(drop=True)
Out[108]:
State Industry Company Zip Code Employees
0 Nevada Hotels, Casinos, Resorts Caesars Entertainment 89501 159,100
1 Nevada Hotels, Casinos, Resorts Las Vegas Sands 89113 159,100
2 Nevada Hotels, Casinos, Resorts MGM Resorts International 89109 159,100
3 Idaho Semiconductors and Other Electronic Components Micron Technology 83716 48,000
4 Kentucky Food Services Yum Brands 40213 31,700
5 Oregon Automotive Retailing, Services Lithia Motors 97501 30,200
6 Delaware Chemicals DuPont 19805 24,000
7 Iowa Insurance: Life, Health (Stock) Principal Financial 50392 19,700
8 Washington Transportation and Logistics Expeditors International of Washington 98006 18,900
9 Illinois Information Technology Services CDW 60061 15,100
10 Maryland Energy Constellation Energy 21231 14,200
11 Kansas Food Production Seaboard 66202 14,000
12 Colorado Telecommunications EchoStar 80112 13,700
13 Indiana Metals Steel Dynamics 46804 13,000
14 Louisiana Utilities: Gas and Electric Entergy 70113 12,300
15 Alabama Building Materials, Glass Vulcan Materials 35242 12,000
16 Arkansas Specialty Retailers: Other Murphy USA 71730 11,600
17 North Carolina Automotive Retailing, Services Sonic Automotive 28211 10,800
18 District of Columbia Diversified Financials Fannie Mae 20005 8,200
19 Michigan Insurance: Property and Casualty (Mutual) Auto-Owners Insurance 48917 7,300
20 Wisconsin Utilities: Gas and Electric WEC Energy 53203 7,000
21 Georgia Homebuilders Pulte 30326 6,800
22 Nebraska Insurance: Life, Health (Mutual) Mutual of Omaha Insurance 68175 6,500
23 Virginia Tobacco Altria 23230 6,200
24 Rhode Island Insurance: Property and Casualty (Stock) FM 02919 5,800
25 Texas Diversified Financials Corebridge Financial 77019 5,200
26 Pennsylvania Homebuilders Toll Brothers 19034 4,900
27 Massachusetts Real Estate American Tower 02116 4,700
28 Florida Energy World Kinect 33178 4,700
29 Missouri Insurance: Life, Health (Stock) Reinsurance of America 63017 4,100
30 Minnesota Insurance: Life, Health (Mutual) Thrivent Financial for Lutherans 55415 4,000
31 New Jersey Petroleum Refining PBF Energy 07054 3,900
32 Connecticut Securities Interactive Brokers 06830 3,000
33 Arizona Homebuilders Taylor Morrison Home 85251 3,000
34 Oklahoma Mining, Crude-Oil Production Devon Energy 73102 2,300
35 Tennessee Petroleum Refining Delek US 37027 2,000
36 New York Mining, Crude-Oil Production Hess 10036 1,800
37 Ohio Real Estate Welltower 43615 700
38 California Wholesalers: Diversified A-Mark Precious Metals 90245 500
In [109]:
gdfstsminempin = gdfsts.merge(dfstminempin, how = 'inner', on = ['State'])
gdfusactminempin = gdfusact.merge(dfstminempin, how = 'inner', on = ['Zip Code']).sort_values('Employees', ascending=False).reset_index(drop=True)
gdfusactminempin
Out[109]:
Zip Code Latitude Longitude Population geometry Employees State Industry Company
0 89501 40 -120 3,641 POINT (-119.81262 39.52602) 159,100 Nevada Hotels, Casinos, Resorts Caesars Entertainment
1 89113 36 -115 37,313 POINT (-115.26236 36.06017) 159,100 Nevada Hotels, Casinos, Resorts Las Vegas Sands
2 89109 36 -115 6,924 POINT (-115.16327 36.12603) 159,100 Nevada Hotels, Casinos, Resorts MGM Resorts International
3 83716 44 -116 21,091 POINT (-115.6548 43.67271) 48,000 Idaho Semiconductors and Other Electronic Components Micron Technology
4 40213 38 -86 15,805 POINT (-85.71571 38.177) 31,700 Kentucky Food Services Yum Brands
5 97501 42 -123 45,008 POINT (-122.89459 42.2856) 30,200 Oregon Automotive Retailing, Services Lithia Motors
6 19805 40 -76 40,315 POINT (-75.59373 39.74523) 24,000 Delaware Chemicals DuPont
7 50392 42 -94 15,018 POINT (-93.628 41.5898) 19,700 Iowa Insurance: Life, Health (Stock) Principal Financial
8 98006 48 -122 40,770 POINT (-122.14957 47.55772) 18,900 Washington Transportation and Logistics Expeditors International of Washington
9 60061 42 -88 27,883 POINT (-87.96046 42.2334) 15,100 Illinois Information Technology Services CDW
10 21231 39 -77 14,556 POINT (-76.592 39.28775) 14,200 Maryland Energy Constellation Energy
11 66202 39 -95 17,321 POINT (-94.66909 39.02392) 14,000 Kansas Food Production Seaboard
12 80112 40 -105 36,687 POINT (-104.85854 39.57288) 13,700 Colorado Telecommunications EchoStar
13 46804 41 -85 29,177 POINT (-85.23913 41.05421) 13,000 Indiana Metals Steel Dynamics
14 70113 30 -90 9,888 POINT (-90.08382 29.9422) 12,300 Louisiana Utilities: Gas and Electric Entergy
15 35242 33 -87 56,956 POINT (-86.67073 33.42371) 12,000 Alabama Building Materials, Glass Vulcan Materials
16 71730 33 -93 29,187 POINT (-92.63458 33.20303) 11,600 Arkansas Specialty Retailers: Other Murphy USA
17 28211 35 -81 32,637 POINT (-80.79604 35.16816) 10,800 North Carolina Automotive Retailing, Services Sonic Automotive
18 20005 39 -77 12,960 POINT (-77.0316 38.90443) 8,200 District of Columbia Diversified Financials Fannie Mae
19 48917 43 -85 32,029 POINT (-84.63897 42.72509) 7,300 Michigan Insurance: Property and Casualty (Mutual) Auto-Owners Insurance
20 53203 43 -88 2,077 POINT (-87.91603 43.03828) 7,000 Wisconsin Utilities: Gas and Electric WEC Energy
21 30326 34 -84 8,497 POINT (-84.36342 33.84957) 6,800 Georgia Homebuilders Pulte
22 68175 41 -96 0 POINT (-95.96584 41.26502) 6,500 Nebraska Insurance: Life, Health (Mutual) Mutual of Omaha Insurance
23 23230 38 -77 8,304 POINT (-77.49153 37.587) 6,200 Virginia Tobacco Altria
24 02919 42 -72 29,473 POINT (-71.52002 41.82733) 5,800 Rhode Island Insurance: Property and Casualty (Stock) FM
25 77019 30 -95 23,662 POINT (-95.41212 29.75318) 5,200 Texas Diversified Financials Corebridge Financial
26 19034 40 -75 7,084 POINT (-75.20953 40.13353) 4,900 Pennsylvania Homebuilders Toll Brothers
27 33178 26 -80 65,515 POINT (-80.4213 25.83578) 4,700 Florida Energy World Kinect
28 02116 42 -71 22,040 POINT (-71.07638 42.35105) 4,700 Massachusetts Real Estate American Tower
29 63017 39 -91 43,074 POINT (-90.53722 38.65143) 4,100 Missouri Insurance: Life, Health (Stock) Reinsurance of America
30 55415 45 -93 6,474 POINT (-93.2578 44.97463) 4,000 Minnesota Insurance: Life, Health (Mutual) Thrivent Financial for Lutherans
31 07054 41 -74 30,139 POINT (-74.40239 40.85527) 3,900 New Jersey Petroleum Refining PBF Energy
32 85251 33 -112 39,976 POINT (-111.92025 33.49406) 3,000 Arizona Homebuilders Taylor Morrison Home
33 06830 41 -74 24,919 POINT (-73.624 41.048) 3,000 Connecticut Securities Interactive Brokers
34 73102 35 -98 3,590 POINT (-97.5191 35.47065) 2,300 Oklahoma Mining, Crude-Oil Production Devon Energy
35 37027 36 -87 61,961 POINT (-86.78439 35.99978) 2,000 Tennessee Petroleum Refining Delek US
36 10036 41 -74 30,589 POINT (-73.99064 40.75976) 1,800 New York Mining, Crude-Oil Production Hess
37 43615 42 -84 40,813 POINT (-83.67255 41.65045) 700 Ohio Real Estate Welltower
38 90245 34 -118 16,863 POINT (-118.40161 33.91709) 500 California Wholesalers: Diversified A-Mark Precious Metals
In [110]:
mstminempin = gdfstsminempin.explore(column='Employees', name='The Smallest Employer Industry in each State visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactminempin.explore(m=mstminempin, column='Employees', name='The Smallest Employer Industry in each State visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mstminempin)
mstminempin
Out[110]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [111]:
# Check the Biggest Revenue Industry in US (all States combined) (other viewpoint)
# a.k.a the Biggest Total Revenue Industry in US.
dfusmaxrevin = df.groupby(['Industry'], as_index=False).sum('Revenue (rounded)').sort_values(by=['Revenue (rounded)'], ascending=False)[['Industry','Revenue (rounded)']].reset_index(drop=True)
dfusmaxrevin10 = dfusmaxrevin.head(10)
dfusmaxrevin
Out[111]:
Industry Revenue (rounded)
0 Internet Services and Retailing 1,330,100,000,000
1 Commercial Banks 1,321,000,000,000
2 General Merchandisers 1,116,800,000,000
3 Petroleum Refining 1,044,500,000,000
4 Health Care: Insurance and Managed Care 908,000,000,000
5 Wholesalers: Health Care 853,200,000,000
6 Insurance: Property and Casualty (Stock) 842,900,000,000
7 Health Care: Pharmacy and Other Services 669,500,000,000
8 Diversified Financials 627,600,000,000
9 Computers, Office Equipment 598,300,000,000
10 Motor Vehicles & Parts 590,800,000,000
11 Specialty Retailers: Other 505,200,000,000
12 Pharmaceuticals 487,300,000,000
13 Telecommunications 473,800,000,000
14 Semiconductors and Other Electronic Components 446,900,000,000
15 Food & Drug Stores 441,900,000,000
16 Aerospace & Defense 407,400,000,000
17 Computer Software 393,200,000,000
18 Utilities: Gas and Electric 329,200,000,000
19 Insurance: Life, Health (Stock) 299,200,000,000
20 Pipelines 268,400,000,000
21 Food Consumer Products 263,800,000,000
22 Entertainment 259,900,000,000
23 Insurance: Life, Health (Mutual) 249,800,000,000
24 Insurance: Property and Casualty (Mutual) 226,100,000,000
25 Food Production 222,800,000,000
26 Airlines 221,400,000,000
27 Automotive Retailing, Services 215,700,000,000
28 Wholesalers: Food and Grocery 211,900,000,000
29 Mining, Crude-Oil Production 210,700,000,000
30 Industrial Machinery 207,800,000,000
31 Chemicals 203,000,000,000
32 Information Technology Services 201,900,000,000
33 Medical Products and Equipment 184,600,000,000
34 Mail, Package and Freight Delivery 178,800,000,000
35 Securities 175,900,000,000
36 Financial Data Services 175,300,000,000
37 Wholesalers: Diversified 169,600,000,000
38 Energy 163,200,000,000
39 Wholesalers: Electronics and Office Equipment 158,200,000,000
40 Household and Personal Products 155,300,000,000
41 Construction and Farm Machinery 138,900,000,000
42 Health Care: Medical Facilities 132,500,000,000
43 Specialty Retailers: Apparel 121,800,000,000
44 Homebuilders 119,800,000,000
45 Metals 116,600,000,000
46 Food Services 103,600,000,000
47 Engineering & Construction 100,000,000,000
48 Real Estate 95,100,000,000
49 Beverages 91,600,000,000
50 Diversified Outsourcing Services 89,500,000,000
51 Network and Other Communications Equipment 87,800,000,000
52 Packaging, Containers 80,800,000,000
53 Apparel 79,600,000,000
54 Hotels, Casinos, Resorts 76,100,000,000
55 Transportation and Logistics 60,700,000,000
56 Oil and Gas Equipment, Services 59,600,000,000
57 Tobacco 58,300,000,000
58 Railroads 50,800,000,000
59 Electronics, Electrical Equip. 46,000,000,000
60 Scientific, Photographic and Control Equipment 42,900,000,000
61 Waste Management 38,100,000,000
62 Building Materials, Glass 34,800,000,000
63 Advertising, Marketing 26,400,000,000
64 Home Equipment, Furnishings 26,200,000,000
65 Trucking, Truck Leasing 12,100,000,000
66 Publishing, Printing 10,100,000,000
In [ ]:
# Conclusion: the Biggest Revenue Industry in US is 'Internet Services and Retailing'.
In [112]:
dfusmaxrevin10 = dfusmaxrevin10.merge(df[['State','Company','Industry','Zip Code']], how = 'inner', on = ['Industry'])
dfusmaxrevin10[['Industry','Company','State','Zip Code','Revenue (rounded)']].sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
Out[112]:
Industry Company State Zip Code Revenue (rounded)
0 Internet Services and Retailing Amazon Washington 98109 1,330,100,000,000
1 Internet Services and Retailing Chewy Florida 33322 1,330,100,000,000
2 Internet Services and Retailing Alphabet California 94043 1,330,100,000,000
3 Internet Services and Retailing QVC Colorado 80112 1,330,100,000,000
4 Internet Services and Retailing DoorDash California 94107 1,330,100,000,000
5 Internet Services and Retailing Airbnb California 94103 1,330,100,000,000
6 Internet Services and Retailing Wayfair Massachusetts 02116 1,330,100,000,000
7 Internet Services and Retailing Ebay California 95125 1,330,100,000,000
8 Internet Services and Retailing Expedia Washington 98119 1,330,100,000,000
9 Internet Services and Retailing Booking s Connecticut 06854 1,330,100,000,000
10 Internet Services and Retailing Coupang Washington 98101 1,330,100,000,000
11 Internet Services and Retailing Uber California 94158 1,330,100,000,000
12 Internet Services and Retailing Meta California 94025 1,330,100,000,000
13 Commercial Banks Truist Financial North Carolina 28202 1,321,000,000,000
14 Commercial Banks KeyCorp Ohio 44114 1,321,000,000,000
15 Commercial Banks Regions Financial Alabama 35203 1,321,000,000,000
16 Commercial Banks Huntington Bancshares Ohio 43287 1,321,000,000,000
17 Commercial Banks Citizens Financial Rhode Island 02903 1,321,000,000,000
18 Commercial Banks Fifth Third Bancorp Ohio 45263 1,321,000,000,000
19 Commercial Banks M&T Bank New York 14203 1,321,000,000,000
20 Commercial Banks First Citizens BancShares North Carolina 27609 1,321,000,000,000
21 Commercial Banks State Street Massachusetts 02114 1,321,000,000,000
22 Commercial Banks Northern Trust Illinois 60603 1,321,000,000,000
23 Commercial Banks PNC Pennsylvania 15222 1,321,000,000,000
24 Commercial Banks U.S. Bancorp Minnesota 55402 1,321,000,000,000
25 Commercial Banks Capital One Virginia 22102 1,321,000,000,000
26 Commercial Banks Morgan Stanley New York 10036 1,321,000,000,000
27 Commercial Banks Wells Fargo California 94104 1,321,000,000,000
28 Commercial Banks Goldman Sachs New York 10282 1,321,000,000,000
29 Commercial Banks Citi New York 10013 1,321,000,000,000
30 Commercial Banks Bank of America North Carolina 28255 1,321,000,000,000
31 Commercial Banks JPMorgan Chase New York 10017 1,321,000,000,000
32 Commercial Banks Bank of New York New York 10286 1,321,000,000,000
33 General Merchandisers Macy's New York 10001 1,116,800,000,000
34 General Merchandisers Nordstrom Washington 98101 1,116,800,000,000
35 General Merchandisers Kohl's Wisconsin 53051 1,116,800,000,000
36 General Merchandisers BJ's Wholesale Club Massachusetts 01752 1,116,800,000,000
37 General Merchandisers Target Minnesota 55403 1,116,800,000,000
38 General Merchandisers Costco Washington 98027 1,116,800,000,000
39 General Merchandisers Walmart Arkansas 72712 1,116,800,000,000
40 Petroleum Refining Exxon Mobil Texas 77389 1,044,500,000,000
41 Petroleum Refining Chevron Texas 77002 1,044,500,000,000
42 Petroleum Refining Phillips 66 Texas 77042 1,044,500,000,000
43 Petroleum Refining Marathon Petroleum Ohio 45840 1,044,500,000,000
44 Petroleum Refining Valero Energy Texas 78249 1,044,500,000,000
45 Petroleum Refining PBF Energy New Jersey 07054 1,044,500,000,000
46 Petroleum Refining HF Sinclair Texas 75219 1,044,500,000,000
47 Petroleum Refining Delek US Tennessee 37027 1,044,500,000,000
48 Petroleum Refining Par Pacific Texas 77024 1,044,500,000,000
49 Health Care: Insurance and Managed Care Oscar Health New York 10013 908,000,000,000
50 Health Care: Insurance and Managed Care Molina Healthcare California 90802 908,000,000,000
51 Health Care: Insurance and Managed Care Humana Kentucky 40202 908,000,000,000
52 Health Care: Insurance and Managed Care Centene Missouri 63105 908,000,000,000
53 Health Care: Insurance and Managed Care UnitedHealth Minnesota 55344 908,000,000,000
54 Health Care: Insurance and Managed Care Elevance Health Indiana 46204 908,000,000,000
55 Wholesalers: Health Care McKesson Texas 75039 853,200,000,000
56 Wholesalers: Health Care Cencora Pennsylvania 19428 853,200,000,000
57 Wholesalers: Health Care Cardinal Health Ohio 43017 853,200,000,000
58 Wholesalers: Health Care Henry Schein New York 11747 853,200,000,000
59 Wholesalers: Health Care Owens & Minor Virginia 23060 853,200,000,000
60 Insurance: Property and Casualty (Stock) Loews New York 10019 842,900,000,000
61 Insurance: Property and Casualty (Stock) Old Republic International Illinois 60601 842,900,000,000
62 Insurance: Property and Casualty (Stock) American Financial Ohio 45202 842,900,000,000
63 Insurance: Property and Casualty (Stock) FM Rhode Island 02919 842,900,000,000
64 Insurance: Property and Casualty (Stock) Cincinnati Financial Ohio 45014 842,900,000,000
65 Insurance: Property and Casualty (Stock) Assurant Georgia 30339 842,900,000,000
66 Insurance: Property and Casualty (Stock) W.R. Berkley Connecticut 06830 842,900,000,000
67 Insurance: Property and Casualty (Stock) Fidelity National Financial Florida 32204 842,900,000,000
68 Insurance: Property and Casualty (Stock) Markel Virginia 23060 842,900,000,000
69 Insurance: Property and Casualty (Stock) American International New York 10020 842,900,000,000
70 Insurance: Property and Casualty (Stock) American Family Insurance Wisconsin 53783 842,900,000,000
71 Insurance: Property and Casualty (Stock) Hartford Insurance Connecticut 06155 842,900,000,000
72 Insurance: Property and Casualty (Stock) Travelers New York 10017 842,900,000,000
73 Insurance: Property and Casualty (Stock) USAA Texas 78288 842,900,000,000
74 Insurance: Property and Casualty (Stock) Liberty Mutual Insurance Massachusetts 02116 842,900,000,000
75 Insurance: Property and Casualty (Stock) Allstate Illinois 60062 842,900,000,000
76 Insurance: Property and Casualty (Stock) Progressive Ohio 44143 842,900,000,000
77 Insurance: Property and Casualty (Stock) Berkshire Hathaway Nebraska 68131 842,900,000,000
78 Health Care: Pharmacy and Other Services Labcorp s North Carolina 27215 669,500,000,000
79 Health Care: Pharmacy and Other Services Quest Diagnostics New Jersey 07094 669,500,000,000
80 Health Care: Pharmacy and Other Services BrightSpring Health Services Kentucky 40222 669,500,000,000
81 Health Care: Pharmacy and Other Services CVS Health Rhode Island 02895 669,500,000,000
82 Health Care: Pharmacy and Other Services IQVIA s North Carolina 27703 669,500,000,000
83 Health Care: Pharmacy and Other Services Cigna Connecticut 06002 669,500,000,000
84 Diversified Financials Corebridge Financial Texas 77019 627,600,000,000
85 Diversified Financials Voya Financial New York 10169 627,600,000,000
86 Diversified Financials Icahn Enterprises Florida 33160 627,600,000,000
87 Diversified Financials Jefferies Financial New York 10022 627,600,000,000
88 Diversified Financials Arthur J. Gallagher Illinois 60008 627,600,000,000
89 Diversified Financials Blackstone New York 10154 627,600,000,000
90 Diversified Financials Ameriprise Financial Minnesota 55474 627,600,000,000
91 Diversified Financials Ally Financial Michigan 48226 627,600,000,000
92 Diversified Financials Discover Financial Illinois 60015 627,600,000,000
93 Diversified Financials Synchrony Financial Connecticut 06902 627,600,000,000
94 Diversified Financials Marsh & McLennan New York 10036 627,600,000,000
95 Diversified Financials American Express New York 10285 627,600,000,000
96 Diversified Financials StoneX New York 10169 627,600,000,000
97 Diversified Financials Freddie Mac Virginia 22102 627,600,000,000
98 Diversified Financials Fannie Mae District of Columbia 20005 627,600,000,000
99 Computers, Office Equipment Apple California 95014 598,300,000,000
100 Computers, Office Equipment Dell Technologies Texas 78682 598,300,000,000
101 Computers, Office Equipment HP California 94304 598,300,000,000
102 Computers, Office Equipment Hewlett Packard Texas 77389 598,300,000,000
103 Computers, Office Equipment Super Micro Computer California 95131 598,300,000,000
104 Computers, Office Equipment Western Digital California 95119 598,300,000,000
In [113]:
gdfstsusmaxrevin10 = gdfsts.merge(dfusmaxrevin10, how = 'inner', on = ['State'])
gdfusactusmaxrevin10 = gdfusact.merge(dfusmaxrevin10, how = 'inner', on = ['Zip Code']).sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
gdfusactusmaxrevin10
Out[113]:
Zip Code Latitude Longitude Population geometry Industry Revenue (rounded) State Company
0 98109 48 -122 32,552 POINT (-122.34486 47.63128) Internet Services and Retailing 1,330,100,000,000 Washington Amazon
1 98119 48 -122 26,390 POINT (-122.36932 47.63943) Internet Services and Retailing 1,330,100,000,000 Washington Expedia
2 94103 38 -122 33,524 POINT (-122.41136 37.77299) Internet Services and Retailing 1,330,100,000,000 California Airbnb
3 80112 40 -105 36,687 POINT (-104.85854 39.57288) Internet Services and Retailing 1,330,100,000,000 Colorado QVC
4 94107 38 -122 30,190 POINT (-122.39508 37.76473) Internet Services and Retailing 1,330,100,000,000 California DoorDash
5 94158 38 -122 11,206 POINT (-122.39153 37.77116) Internet Services and Retailing 1,330,100,000,000 California Uber
6 95125 37 -122 53,934 POINT (-121.89408 37.29554) Internet Services and Retailing 1,330,100,000,000 California Ebay
7 33322 26 -80 40,522 POINT (-80.27429 26.14997) Internet Services and Retailing 1,330,100,000,000 Florida Chewy
8 98101 48 -122 16,396 POINT (-122.33454 47.61119) Internet Services and Retailing 1,330,100,000,000 Washington Coupang
9 94025 37 -122 40,230 POINT (-122.1829 37.45087) Internet Services and Retailing 1,330,100,000,000 California Meta
10 94043 37 -122 32,042 POINT (-122.06892 37.41188) Internet Services and Retailing 1,330,100,000,000 California Alphabet
11 02116 42 -71 22,040 POINT (-71.07638 42.35105) Internet Services and Retailing 1,330,100,000,000 Massachusetts Wayfair
12 06854 41 -73 31,753 POINT (-73.42972 41.09148) Internet Services and Retailing 1,330,100,000,000 Connecticut Booking s
13 55402 45 -93 760 POINT (-93.27119 44.97608) Commercial Banks 1,321,000,000,000 Minnesota U.S. Bancorp
14 02903 42 -71 12,309 POINT (-71.41003 41.81902) Commercial Banks 1,321,000,000,000 Rhode Island Citizens Financial
15 27609 36 -79 35,548 POINT (-78.63282 35.8437) Commercial Banks 1,321,000,000,000 North Carolina First Citizens BancShares
16 60603 42 -88 1,126 POINT (-87.6274 41.88018) Commercial Banks 1,321,000,000,000 Illinois Northern Trust
17 94104 38 -122 478 POINT (-122.40211 37.79144) Commercial Banks 1,321,000,000,000 California Wells Fargo
18 28202 35 -81 16,855 POINT (-80.8447 35.22773) Commercial Banks 1,321,000,000,000 North Carolina Truist Financial
19 15222 40 -80 5,649 POINT (-79.9912 40.44998) Commercial Banks 1,321,000,000,000 Pennsylvania PNC
20 14203 43 -79 2,526 POINT (-78.86507 42.86244) Commercial Banks 1,321,000,000,000 New York M&T Bank
21 10282 41 -74 5,960 POINT (-74.01495 40.71655) Commercial Banks 1,321,000,000,000 New York Goldman Sachs
22 45263 39 -84 0 POINT (-84.4569 39.1616) Commercial Banks 1,321,000,000,000 Ohio Fifth Third Bancorp
23 43287 40 -83 905,748 POINT (-83.0011 39.9619) Commercial Banks 1,321,000,000,000 Ohio Huntington Bancshares
24 10036 41 -74 30,589 POINT (-73.99064 40.75976) Commercial Banks 1,321,000,000,000 New York Morgan Stanley
25 28255 35 -81 0 POINT (-80.8434 35.2267) Commercial Banks 1,321,000,000,000 North Carolina Bank of America
26 35203 34 -87 3,301 POINT (-86.80999 33.51847) Commercial Banks 1,321,000,000,000 Alabama Regions Financial
27 10286 41 -74 5,269 POINT (-74.01182 40.7052) Commercial Banks 1,321,000,000,000 New York Bank of New York
28 10017 41 -74 14,985 POINT (-73.9726 40.75235) Commercial Banks 1,321,000,000,000 New York JPMorgan Chase
29 44114 42 -82 7,472 POINT (-81.67625 41.5137) Commercial Banks 1,321,000,000,000 Ohio KeyCorp
30 10013 41 -74 28,215 POINT (-74.00472 40.72001) Commercial Banks 1,321,000,000,000 New York Citi
31 02114 42 -71 13,853 POINT (-71.06686 42.36337) Commercial Banks 1,321,000,000,000 Massachusetts State Street
32 22102 39 -77 28,577 POINT (-77.22901 38.95199) Commercial Banks 1,321,000,000,000 Virginia Capital One
33 53051 43 -88 39,000 POINT (-88.12348 43.14905) General Merchandisers 1,116,800,000,000 Wisconsin Kohl's
34 55403 45 -93 17,354 POINT (-93.28588 44.97023) General Merchandisers 1,116,800,000,000 Minnesota Target
35 72712 36 -94 38,072 POINT (-94.22196 36.39837) General Merchandisers 1,116,800,000,000 Arkansas Walmart
36 01752 42 -72 41,398 POINT (-71.54681 42.3494) General Merchandisers 1,116,800,000,000 Massachusetts BJ's Wholesale Club
37 98027 48 -122 28,335 POINT (-122.00176 47.50387) General Merchandisers 1,116,800,000,000 Washington Costco
38 98101 48 -122 16,396 POINT (-122.33454 47.61119) General Merchandisers 1,116,800,000,000 Washington Nordstrom
39 10001 41 -74 29,079 POINT (-73.99728 40.75064) General Merchandisers 1,116,800,000,000 New York Macy's
40 77024 30 -96 37,647 POINT (-95.50869 29.77073) Petroleum Refining 1,044,500,000,000 Texas Par Pacific
41 77002 30 -95 19,616 POINT (-95.36538 29.75635) Petroleum Refining 1,044,500,000,000 Texas Chevron
42 07054 41 -74 30,139 POINT (-74.40239 40.85527) Petroleum Refining 1,044,500,000,000 New Jersey PBF Energy
43 78249 30 -99 61,772 POINT (-98.614 29.56752) Petroleum Refining 1,044,500,000,000 Texas Valero Energy
44 77389 30 -96 44,545 POINT (-95.50752 30.11509) Petroleum Refining 1,044,500,000,000 Texas Exxon Mobil
45 37027 36 -87 61,961 POINT (-86.78439 35.99978) Petroleum Refining 1,044,500,000,000 Tennessee Delek US
46 75219 33 -97 25,001 POINT (-96.81315 32.81087) Petroleum Refining 1,044,500,000,000 Texas HF Sinclair
47 77042 30 -96 40,725 POINT (-95.56015 29.74125) Petroleum Refining 1,044,500,000,000 Texas Phillips 66
48 45840 41 -84 54,342 POINT (-83.64943 41.02626) Petroleum Refining 1,044,500,000,000 Ohio Marathon Petroleum
49 55344 45 -93 14,180 POINT (-93.43037 44.86452) Health Care: Insurance and Managed Care 908,000,000,000 Minnesota UnitedHealth
50 46204 40 -86 11,022 POINT (-86.15703 39.77134) Health Care: Insurance and Managed Care 908,000,000,000 Indiana Elevance Health
51 63105 39 -90 18,860 POINT (-90.32812 38.64427) Health Care: Insurance and Managed Care 908,000,000,000 Missouri Centene
52 90802 34 -118 39,859 POINT (-118.21143 33.75035) Health Care: Insurance and Managed Care 908,000,000,000 California Molina Healthcare
53 10013 41 -74 28,215 POINT (-74.00472 40.72001) Health Care: Insurance and Managed Care 908,000,000,000 New York Oscar Health
54 40202 38 -86 7,109 POINT (-85.75205 38.25288) Health Care: Insurance and Managed Care 908,000,000,000 Kentucky Humana
55 43017 40 -83 41,422 POINT (-83.13314 40.1189) Wholesalers: Health Care 853,200,000,000 Ohio Cardinal Health
56 11747 41 -73 19,826 POINT (-73.40931 40.78372) Wholesalers: Health Care 853,200,000,000 New York Henry Schein
57 19428 40 -75 20,225 POINT (-75.30317 40.08011) Wholesalers: Health Care 853,200,000,000 Pennsylvania Cencora
58 75039 33 -97 22,450 POINT (-96.94042 32.88592) Wholesalers: Health Care 853,200,000,000 Texas McKesson
59 23060 38 -78 36,111 POINT (-77.53427 37.65981) Wholesalers: Health Care 853,200,000,000 Virginia Owens & Minor
60 06155 42 -73 121,054 POINT (-72.6859 41.7638) Insurance: Property and Casualty (Stock) 842,900,000,000 Connecticut Hartford Insurance
61 53783 43 -89 0 POINT (-89.4012 43.0731) Insurance: Property and Casualty (Stock) 842,900,000,000 Wisconsin American Family Insurance
62 78288 29 -98 0 POINT (-98.4935 29.4239) Insurance: Property and Casualty (Stock) 842,900,000,000 Texas USAA
63 68131 41 -96 13,928 POINT (-95.96479 41.26435) Insurance: Property and Casualty (Stock) 842,900,000,000 Nebraska Berkshire Hathaway
64 45202 39 -85 17,022 POINT (-84.50243 39.10885) Insurance: Property and Casualty (Stock) 842,900,000,000 Ohio American Financial
65 60601 42 -88 16,292 POINT (-87.62197 41.88527) Insurance: Property and Casualty (Stock) 842,900,000,000 Illinois Old Republic International
66 02116 42 -71 22,040 POINT (-71.07638 42.35105) Insurance: Property and Casualty (Stock) 842,900,000,000 Massachusetts Liberty Mutual Insurance
67 10017 41 -74 14,985 POINT (-73.9726 40.75235) Insurance: Property and Casualty (Stock) 842,900,000,000 New York Travelers
68 10019 41 -74 44,276 POINT (-73.9853 40.76586) Insurance: Property and Casualty (Stock) 842,900,000,000 New York Loews
69 10020 41 -74 0 POINT (-73.98071 40.75917) Insurance: Property and Casualty (Stock) 842,900,000,000 New York American International
70 02919 42 -72 29,473 POINT (-71.52002 41.82733) Insurance: Property and Casualty (Stock) 842,900,000,000 Rhode Island FM
71 60062 42 -88 41,667 POINT (-87.84235 42.12663) Insurance: Property and Casualty (Stock) 842,900,000,000 Illinois Allstate
72 23060 38 -78 36,111 POINT (-77.53427 37.65981) Insurance: Property and Casualty (Stock) 842,900,000,000 Virginia Markel
73 30339 34 -84 34,872 POINT (-84.46483 33.86786) Insurance: Property and Casualty (Stock) 842,900,000,000 Georgia Assurant
74 32204 30 -82 8,421 POINT (-81.68095 30.31636) Insurance: Property and Casualty (Stock) 842,900,000,000 Florida Fidelity National Financial
75 06830 41 -74 24,919 POINT (-73.624 41.048) Insurance: Property and Casualty (Stock) 842,900,000,000 Connecticut W.R. Berkley
76 44143 42 -81 24,337 POINT (-81.47513 41.55358) Insurance: Property and Casualty (Stock) 842,900,000,000 Ohio Progressive
77 45014 39 -85 45,652 POINT (-84.5521 39.32822) Insurance: Property and Casualty (Stock) 842,900,000,000 Ohio Cincinnati Financial
78 02895 42 -71 43,081 POINT (-71.49923 42.00103) Health Care: Pharmacy and Other Services 669,500,000,000 Rhode Island CVS Health
79 27703 36 -79 62,994 POINT (-78.80452 35.96299) Health Care: Pharmacy and Other Services 669,500,000,000 North Carolina IQVIA s
80 27215 36 -79 45,967 POINT (-79.48729 36.03055) Health Care: Pharmacy and Other Services 669,500,000,000 North Carolina Labcorp s
81 06002 42 -73 21,547 POINT (-72.73714 41.84286) Health Care: Pharmacy and Other Services 669,500,000,000 Connecticut Cigna
82 07094 41 -74 21,437 POINT (-74.06588 40.78109) Health Care: Pharmacy and Other Services 669,500,000,000 New Jersey Quest Diagnostics
83 40222 38 -86 21,634 POINT (-85.61173 38.26436) Health Care: Pharmacy and Other Services 669,500,000,000 Kentucky BrightSpring Health Services
84 10022 41 -74 34,340 POINT (-73.96787 40.75856) Diversified Financials 627,600,000,000 New York Jefferies Financial
85 06902 41 -74 72,915 POINT (-73.54751 41.05949) Diversified Financials 627,600,000,000 Connecticut Synchrony Financial
86 10285 41 -74 0 POINT (-74.01492 40.71201) Diversified Financials 627,600,000,000 New York American Express
87 60015 42 -88 27,720 POINT (-87.87486 42.17239) Diversified Financials 627,600,000,000 Illinois Discover Financial
88 60008 42 -88 22,949 POINT (-88.0229 42.0739) Diversified Financials 627,600,000,000 Illinois Arthur J. Gallagher
89 48226 42 -83 6,893 POINT (-83.05034 42.33182) Diversified Financials 627,600,000,000 Michigan Ally Financial
90 33160 26 -80 43,225 POINT (-80.13583 25.93234) Diversified Financials 627,600,000,000 Florida Icahn Enterprises
91 10036 41 -74 30,589 POINT (-73.99064 40.75976) Diversified Financials 627,600,000,000 New York Marsh & McLennan
92 10154 41 -74 0 POINT (-73.97249 40.75778) Diversified Financials 627,600,000,000 New York Blackstone
93 55474 45 -93 28,071 POINT (-93.27 44.98) Diversified Financials 627,600,000,000 Minnesota Ameriprise Financial
94 77019 30 -95 23,662 POINT (-95.41212 29.75318) Diversified Financials 627,600,000,000 Texas Corebridge Financial
95 10169 41 -74 0 POINT (-73.97643 40.75467) Diversified Financials 627,600,000,000 New York StoneX
96 10169 41 -74 0 POINT (-73.97643 40.75467) Diversified Financials 627,600,000,000 New York Voya Financial
97 22102 39 -77 28,577 POINT (-77.22901 38.95199) Diversified Financials 627,600,000,000 Virginia Freddie Mac
98 20005 39 -77 12,960 POINT (-77.0316 38.90443) Diversified Financials 627,600,000,000 District of Columbia Fannie Mae
99 94304 37 -122 4,731 POINT (-122.16699 37.39744) Computers, Office Equipment 598,300,000,000 California HP
100 95131 37 -122 30,745 POINT (-121.89793 37.38729) Computers, Office Equipment 598,300,000,000 California Super Micro Computer
101 95119 37 -122 10,449 POINT (-121.79077 37.22756) Computers, Office Equipment 598,300,000,000 California Western Digital
102 95014 37 -122 61,109 POINT (-122.07981 37.30827) Computers, Office Equipment 598,300,000,000 California Apple
103 77389 30 -96 44,545 POINT (-95.50752 30.11509) Computers, Office Equipment 598,300,000,000 Texas Hewlett Packard
104 78682 30 -98 0 POINT (-97.7273 30.4076) Computers, Office Equipment 598,300,000,000 Texas Dell Technologies
In [114]:
musmaxrevin = gdfstsusmaxrevin10.explore(column='Revenue (rounded)', name='The Biggest Revenue Industry in US visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactusmaxrevin10.explore(m=musmaxrevin, column='Revenue (rounded)', name='The Biggest Revenue Industry in US visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(musmaxrevin)
musmaxrevin
Out[114]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [ ]:
 
In [115]:
# Check the Biggest Employer Industry in US (all States combined)
dfusmaxempin = df.groupby(['Industry'], as_index=False).sum('Employees').sort_values(by=['Employees'], ascending=False)[['Industry','Employees']].reset_index(drop=True)
dfusmaxempin10 = dfusmaxempin.head(10)
dfusmaxempin
Out[115]:
Industry Employees
0 General Merchandisers 3101200
1 Internet Services and Retailing 2071800
2 Commercial Banks 1577000
3 Specialty Retailers: Other 1558200
4 Information Technology Services 1478900
5 Food & Drug Stores 1148100
6 Food Services 1109800
7 Aerospace & Defense 911500
8 Motor Vehicles & Parts 893000
9 Mail, Package and Freight Delivery 794300
10 Insurance: Property and Casualty (Stock) 789100
11 Specialty Retailers: Apparel 669500
12 Health Care: Insurance and Managed Care 650300
13 Semiconductors and Other Electronic Components 627900
14 Food Consumer Products 604700
15 Industrial Machinery 594700
16 Health Care: Medical Facilities 573200
17 Health Care: Pharmacy and Other Services 572800
18 Telecommunications 566700
19 Computer Software 565200
20 Diversified Outsourcing Services 564900
21 Pharmaceuticals 549400
22 Medical Products and Equipment 501600
23 Hotels, Casinos, Resorts 495100
24 Airlines 467900
25 Computers, Office Equipment 447700
26 Chemicals 379700
27 Diversified Financials 350100
28 Entertainment 338000
29 Utilities: Gas and Electric 306200
30 Real Estate 273800
31 Financial Data Services 260100
32 Wholesalers: Diversified 255100
33 Household and Personal Products 255000
34 Network and Other Communications Equipment 251700
35 Transportation and Logistics 251400
36 Food Production 241400
37 Engineering & Construction 240500
38 Automotive Retailing, Services 232000
39 Construction and Farm Machinery 210900
40 Packaging, Containers 191400
41 Wholesalers: Health Care 188600
42 Wholesalers: Food and Grocery 186100
43 Insurance: Life, Health (Stock) 178200
44 Securities 172200
45 Petroleum Refining 160600
46 Electronics, Electrical Equip. 158300
47 Metals 140900
48 Apparel 140500
49 Oil and Gas Equipment, Services 139000
50 Beverages 131200
51 Advertising, Marketing 128200
52 Scientific, Photographic and Control Equipment 125000
53 Energy 121900
54 Insurance: Property and Casualty (Mutual) 113800
55 Waste Management 103700
56 Tobacco 89300
57 Mining, Crude-Oil Production 89000
58 Wholesalers: Electronics and Office Equipment 88900
59 Home Equipment, Furnishings 83600
60 Railroads 75500
61 Insurance: Life, Health (Mutual) 70800
62 Building Materials, Glass 66000
63 Pipelines 55200
64 Homebuilders 49800
65 Trucking, Truck Leasing 33600
66 Publishing, Printing 23900
In [ ]:
# Conclusion: the Biggest Employer Industry in US is General Merchandisers.
In [116]:
dfusmaxempin10 = dfusmaxempin10.merge(df[['State','Company','Industry','Zip Code']], how = 'inner', on = ['Industry'])
dfusmaxempin10[['Industry','Company','State','Zip Code','Employees']].sort_values('Employees', ascending=False).reset_index(drop=True)
Out[116]:
Industry Company State Zip Code Employees
0 General Merchandisers Walmart Arkansas 72712 3101200
1 General Merchandisers Target Minnesota 55403 3101200
2 General Merchandisers Macy's New York 10001 3101200
3 General Merchandisers BJ's Wholesale Club Massachusetts 01752 3101200
4 General Merchandisers Kohl's Wisconsin 53051 3101200
5 General Merchandisers Nordstrom Washington 98101 3101200
6 General Merchandisers Costco Washington 98027 3101200
7 Internet Services and Retailing Expedia Washington 98119 2071800
8 Internet Services and Retailing QVC Colorado 80112 2071800
9 Internet Services and Retailing Ebay California 95125 2071800
10 Internet Services and Retailing DoorDash California 94107 2071800
11 Internet Services and Retailing Airbnb California 94103 2071800
12 Internet Services and Retailing Chewy Florida 33322 2071800
13 Internet Services and Retailing Wayfair Massachusetts 02116 2071800
14 Internet Services and Retailing Booking s Connecticut 06854 2071800
15 Internet Services and Retailing Coupang Washington 98101 2071800
16 Internet Services and Retailing Uber California 94158 2071800
17 Internet Services and Retailing Meta California 94025 2071800
18 Internet Services and Retailing Alphabet California 94043 2071800
19 Internet Services and Retailing Amazon Washington 98109 2071800
20 Commercial Banks Truist Financial North Carolina 28202 1577000
21 Commercial Banks KeyCorp Ohio 44114 1577000
22 Commercial Banks Regions Financial Alabama 35203 1577000
23 Commercial Banks Huntington Bancshares Ohio 43287 1577000
24 Commercial Banks Citizens Financial Rhode Island 02903 1577000
25 Commercial Banks Fifth Third Bancorp Ohio 45263 1577000
26 Commercial Banks M&T Bank New York 14203 1577000
27 Commercial Banks First Citizens BancShares North Carolina 27609 1577000
28 Commercial Banks Northern Trust Illinois 60603 1577000
29 Commercial Banks State Street Massachusetts 02114 1577000
30 Commercial Banks Goldman Sachs New York 10282 1577000
31 Commercial Banks PNC Pennsylvania 15222 1577000
32 Commercial Banks Bank of New York New York 10286 1577000
33 Commercial Banks U.S. Bancorp Minnesota 55402 1577000
34 Commercial Banks Capital One Virginia 22102 1577000
35 Commercial Banks Morgan Stanley New York 10036 1577000
36 Commercial Banks Wells Fargo California 94104 1577000
37 Commercial Banks Citi New York 10013 1577000
38 Commercial Banks Bank of America North Carolina 28255 1577000
39 Commercial Banks JPMorgan Chase New York 10017 1577000
40 Specialty Retailers: Other United Rentals Connecticut 06902 1558200
41 Specialty Retailers: Other ARKO Virginia 23227 1558200
42 Specialty Retailers: Other Williams-Sonoma California 94109 1558200
43 Specialty Retailers: Other Advance Auto Parts North Carolina 27609 1558200
44 Specialty Retailers: Other Ulta Beauty Illinois 60440 1558200
45 Specialty Retailers: Other Casey's General Stores Iowa 50021 1558200
46 Specialty Retailers: Other Tractor Supply Tennessee 37027 1558200
47 Specialty Retailers: Other Dick's Sporting Goods Pennsylvania 15108 1558200
48 Specialty Retailers: Other O'Reilly Automotive Missouri 65802 1558200
49 Specialty Retailers: Other Best Buy Minnesota 55423 1558200
50 Specialty Retailers: Other Home Depot Georgia 30339 1558200
51 Specialty Retailers: Other Lowe's North Carolina 28117 1558200
52 Specialty Retailers: Other Murphy USA Arkansas 71730 1558200
53 Specialty Retailers: Other Dollar General Tennessee 37072 1558200
54 Specialty Retailers: Other AutoZone Tennessee 38103 1558200
55 Specialty Retailers: Other Dollar Tree Virginia 23320 1558200
56 Information Technology Services DXC Technology Virginia 20147 1478900
57 Information Technology Services Science Applications International Virginia 20190 1478900
58 Information Technology Services CACI International Virginia 20190 1478900
59 Information Technology Services KBR Texas 77002 1478900
60 Information Technology Services Concentrix California 94560 1478900
61 Information Technology Services Insight Enterprises Arizona 85286 1478900
62 Information Technology Services Kyndryl s New York 10017 1478900
63 Information Technology Services Leidos s Virginia 20190 1478900
64 Information Technology Services Cognizant Technology New Jersey 07666 1478900
65 Information Technology Services CDW Illinois 60061 1478900
66 Information Technology Services IBM New York 10504 1478900
67 Information Technology Services Booz Allen Hamilton Virginia 22102 1478900
68 Food & Drug Stores Walgreens Illinois 60015 1148100
69 Food & Drug Stores Kroger Ohio 45202 1148100
70 Food & Drug Stores Albertsons Idaho 83706 1148100
71 Food & Drug Stores Publix Super Markets Florida 33811 1148100
72 Food & Drug Stores Sprouts Farmers Market Arizona 85054 1148100
73 Food Services Chipotle Mexican Grill California 92660 1109800
74 Food Services Yum Brands Kentucky 40213 1109800
75 Food Services Yum China s Texas 75074 1109800
76 Food Services Darden Restaurants Florida 32837 1109800
77 Food Services McDonald's Illinois 60607 1109800
78 Food Services Starbucks Washington 98134 1109800
79 Aerospace & Defense General Electric Ohio 45215 911500
80 Aerospace & Defense TransDigm Ohio 44115 911500
81 Aerospace & Defense Huntington Ingalls Industries Virginia 23607 911500
82 Aerospace & Defense Textron Rhode Island 02903 911500
83 Aerospace & Defense L3Harris Technologies Florida 32919 911500
84 Aerospace & Defense Howmet Aerospace Pennsylvania 15212 911500
85 Aerospace & Defense Northrop Grumman Virginia 22042 911500
86 Aerospace & Defense Boeing Virginia 22202 911500
87 Aerospace & Defense Lockheed Martin Maryland 20817 911500
88 Aerospace & Defense RTX Virginia 22209 911500
89 Aerospace & Defense General Dynamics Virginia 20190 911500
90 Motor Vehicles & Parts Goodyear Tire & Rubber Ohio 44316 893000
91 Motor Vehicles & Parts THOR Industries Indiana 46514 893000
92 Motor Vehicles & Parts Dana Ohio 43537 893000
93 Motor Vehicles & Parts Autoliv Michigan 48326 893000
94 Motor Vehicles & Parts BorgWarner Michigan 48326 893000
95 Motor Vehicles & Parts Paccar Washington 98004 893000
96 Motor Vehicles & Parts Lear Michigan 48033 893000
97 Motor Vehicles & Parts Tesla Texas 78725 893000
98 Motor Vehicles & Parts Ford Motor Michigan 48126 893000
99 Motor Vehicles & Parts General Motors Michigan 48265 893000
100 Mail, Package and Freight Delivery UPS Georgia 30328 794300
101 Mail, Package and Freight Delivery FedEx Tennessee 38120 794300
In [117]:
gdfstsusmaxempin10 = gdfsts.merge(dfusmaxempin10, how = 'inner', on = ['State'])
gdfusactusmaxempin10 = gdfusact.merge(dfusmaxempin10, how = 'inner', on = ['Zip Code']).sort_values('Employees', ascending=False).reset_index(drop=True)
gdfusactusmaxempin10
Out[117]:
Zip Code Latitude Longitude Population geometry Industry Employees State Company
0 01752 42 -72 41,398 POINT (-71.54681 42.3494) General Merchandisers 3101200 Massachusetts BJ's Wholesale Club
1 55403 45 -93 17,354 POINT (-93.28588 44.97023) General Merchandisers 3101200 Minnesota Target
2 98027 48 -122 28,335 POINT (-122.00176 47.50387) General Merchandisers 3101200 Washington Costco
3 72712 36 -94 38,072 POINT (-94.22196 36.39837) General Merchandisers 3101200 Arkansas Walmart
4 98101 48 -122 16,396 POINT (-122.33454 47.61119) General Merchandisers 3101200 Washington Nordstrom
5 10001 41 -74 29,079 POINT (-73.99728 40.75064) General Merchandisers 3101200 New York Macy's
6 53051 43 -88 39,000 POINT (-88.12348 43.14905) General Merchandisers 3101200 Wisconsin Kohl's
7 94103 38 -122 33,524 POINT (-122.41136 37.77299) Internet Services and Retailing 2071800 California Airbnb
8 94043 37 -122 32,042 POINT (-122.06892 37.41188) Internet Services and Retailing 2071800 California Alphabet
9 98101 48 -122 16,396 POINT (-122.33454 47.61119) Internet Services and Retailing 2071800 Washington Coupang
10 98109 48 -122 32,552 POINT (-122.34486 47.63128) Internet Services and Retailing 2071800 Washington Amazon
11 94025 37 -122 40,230 POINT (-122.1829 37.45087) Internet Services and Retailing 2071800 California Meta
12 98119 48 -122 26,390 POINT (-122.36932 47.63943) Internet Services and Retailing 2071800 Washington Expedia
13 94158 38 -122 11,206 POINT (-122.39153 37.77116) Internet Services and Retailing 2071800 California Uber
14 33322 26 -80 40,522 POINT (-80.27429 26.14997) Internet Services and Retailing 2071800 Florida Chewy
15 95125 37 -122 53,934 POINT (-121.89408 37.29554) Internet Services and Retailing 2071800 California Ebay
16 02116 42 -71 22,040 POINT (-71.07638 42.35105) Internet Services and Retailing 2071800 Massachusetts Wayfair
17 80112 40 -105 36,687 POINT (-104.85854 39.57288) Internet Services and Retailing 2071800 Colorado QVC
18 06854 41 -73 31,753 POINT (-73.42972 41.09148) Internet Services and Retailing 2071800 Connecticut Booking s
19 94107 38 -122 30,190 POINT (-122.39508 37.76473) Internet Services and Retailing 2071800 California DoorDash
20 44114 42 -82 7,472 POINT (-81.67625 41.5137) Commercial Banks 1577000 Ohio KeyCorp
21 60603 42 -88 1,126 POINT (-87.6274 41.88018) Commercial Banks 1577000 Illinois Northern Trust
22 94104 38 -122 478 POINT (-122.40211 37.79144) Commercial Banks 1577000 California Wells Fargo
23 28202 35 -81 16,855 POINT (-80.8447 35.22773) Commercial Banks 1577000 North Carolina Truist Financial
24 02903 42 -71 12,309 POINT (-71.41003 41.81902) Commercial Banks 1577000 Rhode Island Citizens Financial
25 02114 42 -71 13,853 POINT (-71.06686 42.36337) Commercial Banks 1577000 Massachusetts State Street
26 27609 36 -79 35,548 POINT (-78.63282 35.8437) Commercial Banks 1577000 North Carolina First Citizens BancShares
27 45263 39 -84 0 POINT (-84.4569 39.1616) Commercial Banks 1577000 Ohio Fifth Third Bancorp
28 10013 41 -74 28,215 POINT (-74.00472 40.72001) Commercial Banks 1577000 New York Citi
29 43287 40 -83 905,748 POINT (-83.0011 39.9619) Commercial Banks 1577000 Ohio Huntington Bancshares
30 10017 41 -74 14,985 POINT (-73.9726 40.75235) Commercial Banks 1577000 New York JPMorgan Chase
31 22102 39 -77 28,577 POINT (-77.22901 38.95199) Commercial Banks 1577000 Virginia Capital One
32 35203 34 -87 3,301 POINT (-86.80999 33.51847) Commercial Banks 1577000 Alabama Regions Financial
33 10286 41 -74 5,269 POINT (-74.01182 40.7052) Commercial Banks 1577000 New York Bank of New York
34 28255 35 -81 0 POINT (-80.8434 35.2267) Commercial Banks 1577000 North Carolina Bank of America
35 10036 41 -74 30,589 POINT (-73.99064 40.75976) Commercial Banks 1577000 New York Morgan Stanley
36 10282 41 -74 5,960 POINT (-74.01495 40.71655) Commercial Banks 1577000 New York Goldman Sachs
37 14203 43 -79 2,526 POINT (-78.86507 42.86244) Commercial Banks 1577000 New York M&T Bank
38 15222 40 -80 5,649 POINT (-79.9912 40.44998) Commercial Banks 1577000 Pennsylvania PNC
39 55402 45 -93 760 POINT (-93.27119 44.97608) Commercial Banks 1577000 Minnesota U.S. Bancorp
40 50021 42 -94 29,718 POINT (-93.56838 41.7207) Specialty Retailers: Other 1558200 Iowa Casey's General Stores
41 55423 45 -93 36,779 POINT (-93.28144 44.87663) Specialty Retailers: Other 1558200 Minnesota Best Buy
42 60440 42 -88 52,074 POINT (-88.07572 41.70125) Specialty Retailers: Other 1558200 Illinois Ulta Beauty
43 65802 37 -93 46,005 POINT (-93.35167 37.21048) Specialty Retailers: Other 1558200 Missouri O'Reilly Automotive
44 94109 38 -122 54,397 POINT (-122.42138 37.79334) Specialty Retailers: Other 1558200 California Williams-Sonoma
45 28117 36 -81 48,170 POINT (-80.89658 35.57405) Specialty Retailers: Other 1558200 North Carolina Lowe's
46 38103 35 -90 14,025 POINT (-90.05518 35.15308) Specialty Retailers: Other 1558200 Tennessee AutoZone
47 23320 37 -76 59,626 POINT (-76.21807 36.75208) Specialty Retailers: Other 1558200 Virginia Dollar Tree
48 06902 41 -74 72,915 POINT (-73.54751 41.05949) Specialty Retailers: Other 1558200 Connecticut United Rentals
49 15108 41 -80 42,782 POINT (-80.20031 40.50006) Specialty Retailers: Other 1558200 Pennsylvania Dick's Sporting Goods
50 37072 36 -87 32,344 POINT (-86.74494 36.35686) Specialty Retailers: Other 1558200 Tennessee Dollar General
51 23227 38 -77 25,574 POINT (-77.44234 37.61486) Specialty Retailers: Other 1558200 Virginia ARKO
52 71730 33 -93 29,187 POINT (-92.63458 33.20303) Specialty Retailers: Other 1558200 Arkansas Murphy USA
53 27609 36 -79 35,548 POINT (-78.63282 35.8437) Specialty Retailers: Other 1558200 North Carolina Advance Auto Parts
54 37027 36 -87 61,961 POINT (-86.78439 35.99978) Specialty Retailers: Other 1558200 Tennessee Tractor Supply
55 30339 34 -84 34,872 POINT (-84.46483 33.86786) Specialty Retailers: Other 1558200 Georgia Home Depot
56 94560 38 -122 47,145 POINT (-122.02523 37.50771) Information Technology Services 1478900 California Concentrix
57 77002 30 -95 19,616 POINT (-95.36538 29.75635) Information Technology Services 1478900 Texas KBR
58 07666 41 -74 41,499 POINT (-74.01067 40.88998) Information Technology Services 1478900 New Jersey Cognizant Technology
59 10017 41 -74 14,985 POINT (-73.9726 40.75235) Information Technology Services 1478900 New York Kyndryl s
60 60061 42 -88 27,883 POINT (-87.96046 42.2334) Information Technology Services 1478900 Illinois CDW
61 10504 41 -74 7,853 POINT (-73.70629 41.13065) Information Technology Services 1478900 New York IBM
62 20147 39 -77 67,007 POINT (-77.47958 39.04151) Information Technology Services 1478900 Virginia DXC Technology
63 22102 39 -77 28,577 POINT (-77.22901 38.95199) Information Technology Services 1478900 Virginia Booz Allen Hamilton
64 20190 39 -77 22,092 POINT (-77.33806 38.95968) Information Technology Services 1478900 Virginia Leidos s
65 20190 39 -77 22,092 POINT (-77.33806 38.95968) Information Technology Services 1478900 Virginia CACI International
66 85286 33 -112 49,870 POINT (-111.83156 33.27146) Information Technology Services 1478900 Arizona Insight Enterprises
67 20190 39 -77 22,092 POINT (-77.33806 38.95968) Information Technology Services 1478900 Virginia Science Applications International
68 83706 44 -116 36,183 POINT (-116.19427 43.59108) Food & Drug Stores 1148100 Idaho Albertsons
69 85054 34 -112 10,159 POINT (-111.94763 33.67515) Food & Drug Stores 1148100 Arizona Sprouts Farmers Market
70 45202 39 -85 17,022 POINT (-84.50243 39.10885) Food & Drug Stores 1148100 Ohio Kroger
71 33811 28 -82 28,456 POINT (-82.01866 27.97933) Food & Drug Stores 1148100 Florida Publix Super Markets
72 60015 42 -88 27,720 POINT (-87.87486 42.17239) Food & Drug Stores 1148100 Illinois Walgreens
73 92660 34 -118 34,788 POINT (-117.87504 33.63375) Food Services 1109800 California Chipotle Mexican Grill
74 98134 48 -122 779 POINT (-122.33686 47.57691) Food Services 1109800 Washington Starbucks
75 32837 28 -81 49,889 POINT (-81.41998 28.38074) Food Services 1109800 Florida Darden Restaurants
76 60607 42 -88 30,197 POINT (-87.65175 41.87467) Food Services 1109800 Illinois McDonald's
77 40213 38 -86 15,805 POINT (-85.71571 38.177) Food Services 1109800 Kentucky Yum Brands
78 75074 33 -97 53,146 POINT (-96.67304 33.03298) Food Services 1109800 Texas Yum China s
79 23607 37 -76 23,028 POINT (-76.42235 36.98753) Aerospace & Defense 911500 Virginia Huntington Ingalls Industries
80 22202 39 -77 27,352 POINT (-77.05175 38.8569) Aerospace & Defense 911500 Virginia Boeing
81 45215 39 -84 30,806 POINT (-84.46221 39.23536) Aerospace & Defense 911500 Ohio General Electric
82 44115 41 -82 10,389 POINT (-81.66999 41.49211) Aerospace & Defense 911500 Ohio TransDigm
83 02903 42 -71 12,309 POINT (-71.41003 41.81902) Aerospace & Defense 911500 Rhode Island Textron
84 15212 40 -80 27,600 POINT (-80.00844 40.47106) Aerospace & Defense 911500 Pennsylvania Howmet Aerospace
85 32919 28 -81 0 POINT (-80.6386 28.0909) Aerospace & Defense 911500 Florida L3Harris Technologies
86 20190 39 -77 22,092 POINT (-77.33806 38.95968) Aerospace & Defense 911500 Virginia General Dynamics
87 20817 39 -77 37,738 POINT (-77.14919 38.99809) Aerospace & Defense 911500 Maryland Lockheed Martin
88 22042 39 -77 34,631 POINT (-77.19406 38.86463) Aerospace & Defense 911500 Virginia Northrop Grumman
89 22209 39 -77 13,725 POINT (-77.07309 38.89413) Aerospace & Defense 911500 Virginia RTX
90 44316 41 -81 0 POINT (-81.47083 41.07854) Motor Vehicles & Parts 893000 Ohio Goodyear Tire & Rubber
91 78725 30 -98 10,810 POINT (-97.60859 30.23554) Motor Vehicles & Parts 893000 Texas Tesla
92 48033 42 -83 16,900 POINT (-83.28812 42.46478) Motor Vehicles & Parts 893000 Michigan Lear
93 46514 42 -86 41,480 POINT (-85.97547 41.72328) Motor Vehicles & Parts 893000 Indiana THOR Industries
94 98004 48 -122 39,435 POINT (-122.20548 47.61865) Motor Vehicles & Parts 893000 Washington Paccar
95 48326 43 -83 24,488 POINT (-83.2531 42.67536) Motor Vehicles & Parts 893000 Michigan Autoliv
96 48326 43 -83 24,488 POINT (-83.2531 42.67536) Motor Vehicles & Parts 893000 Michigan BorgWarner
97 48126 42 -83 52,075 POINT (-83.18678 42.32999) Motor Vehicles & Parts 893000 Michigan Ford Motor
98 43537 42 -84 29,639 POINT (-83.68542 41.57433) Motor Vehicles & Parts 893000 Ohio Dana
99 48265 42 -83 4,503 POINT (-83.0456 42.3317) Motor Vehicles & Parts 893000 Michigan General Motors
100 30328 34 -84 38,821 POINT (-84.38617 33.93194) Mail, Package and Freight Delivery 794300 Georgia UPS
101 38120 35 -90 13,249 POINT (-89.85237 35.12344) Mail, Package and Freight Delivery 794300 Tennessee FedEx
In [118]:
musmaxempin10 = gdfstsusmaxempin10.explore(column='Employees', name='The Biggest Employer Industry in US visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactusmaxempin10.explore(m=musmaxempin10, column='Employees', name='The Biggest Employer Industry in US visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(musmaxempin10)
musmaxempin10
Out[118]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [119]:
# Check the Most Efficient Company in each Industry
dfinsmaxeffco = df.head(1)
dfinsmaxeffco.insert(0, 'Efficiency', 1) # Add new Column 'Efficiency' to new 

for ins in inslist[0:]:
    dfin = df.where(df['Industry'] == ins[0]).dropna()
    dfin['Efficiency'] = dfin['Revenue (rounded)']/dfin['Employees']
    dfinsmaxeffco = pd.concat([dfinsmaxeffco, dfin.sort_values(by='Efficiency',ascending=False).head(1)], ignore_index=True)
    
dfinsmaxeffco = dfinsmaxeffco.drop(0)
dfinsmaxeffco[['Industry','State','City','Company','Zip Code','Efficiency']].sort_values(by='Efficiency', ascending=False).reset_index(drop=True)
Out[119]:
Industry State City Company Zip Code Efficiency
0 Diversified Financials New York New York StoneX 10169 22,200,000
1 Wholesalers: Diversified California El Segundo A-Mark Precious Metals 90245 19,400,000
2 Petroleum Refining Texas San Antonio Valero Energy 78249 12,525,253
3 Pipelines Texas Houston Plains GP 77002 11,928,571
4 Real Estate Ohio Toledo Welltower 43615 11,428,571
5 Energy Florida Miami World Kinect 33178 8,978,723
6 Mining, Crude-Oil Production Texas Houston EOG Resources 77002 7,406,250
7 Wholesalers: Health Care Pennsylvania Conshohocken Cencora 19428 6,681,818
8 Securities New York New York KKR 10001 6,229,167
9 Insurance: Life, Health (Stock) Missouri Chesterfield Reinsurance of America 63017 5,390,244
10 Insurance: Life, Health (Mutual) Ohio Cincinnati Western & Southern Financial 45202 5,111,111
11 Food Production Ohio Maumee Andersons 43537 4,913,043
12 Health Care: Insurance and Managed Care New York New York Oscar Health 10013 3,833,333
13 Semiconductors and Other Electronic Components California Santa Clara Nvidia 95051 3,625,000
14 Health Care: Pharmacy and Other Services Connecticut Bloomfield Cigna 06002 3,412,983
15 Tobacco Virginia Richmond Altria 23230 3,290,323
16 Entertainment California Los Gatos Netflix 95032 2,785,714
17 Homebuilders Arizona Scottsdale Taylor Morrison Home 85251 2,733,333
18 Commercial Banks New York New York Goldman Sachs 10282 2,729,032
19 Computers, Office Equipment California San Jose Super Micro Computer 95131 2,631,579
20 Insurance: Property and Casualty (Mutual) Ohio Columbus Nationwide 43215 2,604,444
21 Wholesalers: Electronics and Office Equipment California Fremont TD Synnex 94538 2,267,442
22 Internet Services and Retailing California Menlo Park Meta 94025 2,219,973
23 Financial Data Services California Oakland Block 94612 2,114,035
24 Insurance: Property and Casualty (Stock) Ohio Fairfield Cincinnati Financial 45014 2,017,857
25 Pharmaceuticals Massachusetts Boston Vertex Pharmaceuticals 02210 1,803,279
26 Food Consumer Products Minnesota Arden Hills Land O'Lakes 55126 1,800,000
27 Specialty Retailers: Other Arkansas El Dorado Murphy USA 71730 1,543,103
28 Wholesalers: Food and Grocery Virginia Richmond Performance Food 23238 1,486,413
29 Utilities: Gas and Electric Florida Juno Beach NextEra Energy 33408 1,476,190
30 Information Technology Services Illinois Vernon Hills CDW 60061 1,390,728
31 Telecommunications New York New York Verizon 10036 1,353,414
32 Metals Indiana Fort Wayne Steel Dynamics 46804 1,346,154
33 Automotive Retailing, Services North Carolina Charlotte Sonic Automotive 28211 1,314,815
34 Transportation and Logistics Minnesota Eden Prairie C.H. Robinson Worldwide 55347 1,282,609
35 Beverages California Corona Monster Beverage 92879 1,250,000
36 Chemicals Michigan Midland Dow 48674 1,194,444
37 Motor Vehicles & Parts Michigan Detroit General Motors 48265 1,156,790
38 Computer Software Washington Redmond Microsoft 98052 1,075,000
39 Construction and Farm Machinery Illinois Moline Deere 61265 931,532
40 Household and Personal Products Ohio Cincinnati Procter & Gamble 45202 777,778
41 General Merchandisers Washington Issaquah Costco 98027 764,264
42 Packaging, Containers Colorado Westminster Ball 80021 756,250
43 Railroads Nebraska Omaha Union Pacific 68179 746,914
44 Aerospace & Defense Ohio Evendale General Electric 45215 730,189
45 Diversified Outsourcing Services Wisconsin Milwaukee Manpower 53212 670,412
46 Apparel Oregon Beaverton Nike 97005 647,355
47 Building Materials, Glass Alabama Birmingham Vulcan Materials 35242 616,667
48 Engineering & Construction Texas Irving Fluor 75039 605,948
49 Airlines Georgia Atlanta Delta Airlines 30354 598,058
50 Network and Other Communications Equipment California San Jose Cisco Systems 95134 595,133
51 Food & Drug Stores Illinois Deerfield Walgreens 60015 584,950
52 Medical Products and Equipment California Sunnyvale Intuitive Surgical 94086 538,462
53 Industrial Machinery Florida Palm Beach Gardens Carrier Global 33418 516,667
54 Oil and Gas Equipment, Services Texas Houston Baker Hughes 77079 487,719
55 Home Equipment, Furnishings Michigan Livonia Masco 48152 433,333
56 Publishing, Printing New York New York News Corp. 10036 422,594
57 Waste Management Arizona Phoenix Republic Services 85054 380,952
58 Electronics, Electrical Equip. Michigan Benton Harbor Whirlpool 49022 377,273
59 Trucking, Truck Leasing Arkansas Lowell J.B. Hunt Transport Services 72745 360,119
60 Scientific, Photographic and Control Equipment Massachusetts Waltham Thermo Fisher Scientific 02451 343,200
61 Hotels, Casinos, Resorts Nevada Las Vegas Las Vegas Sands 89113 281,796
62 Specialty Retailers: Apparel Washington Sumner Lululemon athletica 98390 271,795
63 Health Care: Medical Facilities Tennessee Nashville HCA Healthcare 37203 260,517
64 Mail, Package and Freight Delivery Georgia Atlanta UPS 30328 244,761
65 Food Services Kentucky Louisville Yum Brands 40213 236,593
66 Advertising, Marketing New York New York Omnicom 10017 209,613
In [120]:
gdfstsinsmaxeffco = gdfsts.merge(dfinsmaxeffco, how = 'inner', on = ['State'])
gdfusactinsmaxeffco = gdfusact.merge(dfinsmaxeffco, how = 'inner', on = ['Zip Code']).sort_values('Efficiency', ascending=False).reset_index(drop=True)
gdfusactinsmaxeffco
Out[120]:
Zip Code Latitude Longitude Population geometry Efficiency Company Industry City State Website Employees Revenue (rounded) CEO
0 10169 41 -74 0 POINT (-73.97643 40.75467) 22,200,000 StoneX Diversified Financials New York New York stonex.com 4,500 99,900,000,000 Philip Smith
1 90245 34 -118 16,863 POINT (-118.40161 33.91709) 19,400,000 A-Mark Precious Metals Wholesalers: Diversified El Segundo California amark.com 500 9,700,000,000 Gregory Roberts
2 78249 30 -99 61,772 POINT (-98.614 29.56752) 12,525,253 Valero Energy Petroleum Refining San Antonio Texas valero.com 9,900 124,000,000,000 Lane Riggs
3 77002 30 -95 19,616 POINT (-95.36538 29.75635) 11,928,571 Plains GP Pipelines Houston Texas plains.com 4,200 50,100,000,000 Wilfred Chiang
4 43615 42 -84 40,813 POINT (-83.67255 41.65045) 11,428,571 Welltower Real Estate Toledo Ohio welltower.com 700 8,000,000,000 Shankh Mitra
5 33178 26 -80 65,515 POINT (-80.4213 25.83578) 8,978,723 World Kinect Energy Miami Florida world-kinect.com 4,700 42,200,000,000 Michael Kasbar
6 77002 30 -95 19,616 POINT (-95.36538 29.75635) 7,406,250 EOG Resources Mining, Crude-Oil Production Houston Texas eogresources.com 3,200 23,700,000,000 Ezra Yacob
7 19428 40 -75 20,225 POINT (-75.30317 40.08011) 6,681,818 Cencora Wholesalers: Health Care Conshohocken Pennsylvania cencora.com 44,000 294,000,000,000 Robert Mauch
8 10001 41 -74 29,079 POINT (-73.99728 40.75064) 6,229,167 KKR Securities New York New York kkr.com 4,800 29,900,000,000 Joseph Bae
9 63017 39 -91 43,074 POINT (-90.53722 38.65143) 5,390,244 Reinsurance of America Insurance: Life, Health (Stock) Chesterfield Missouri rgare.com 4,100 22,100,000,000 Tony Cheng
10 45202 39 -85 17,022 POINT (-84.50243 39.10885) 5,111,111 Western & Southern Financial Insurance: Life, Health (Mutual) Cincinnati Ohio westernsouthern.com 2,700 13,800,000,000 John Barrett
11 43537 42 -84 29,639 POINT (-83.68542 41.57433) 4,913,043 Andersons Food Production Maumee Ohio andersonsinc.com 2,300 11,300,000,000 William Krueger
12 10013 41 -74 28,215 POINT (-74.00472 40.72001) 3,833,333 Oscar Health Health Care: Insurance and Managed Care New York New York hioscar.com 2,400 9,200,000,000 Mark Bertolini
13 95051 37 -122 61,345 POINT (-121.98444 37.3483) 3,625,000 Nvidia Semiconductors and Other Electronic Components Santa Clara California nvidia.com 36,000 130,500,000,000 Jensen Huang
14 06002 42 -73 21,547 POINT (-72.73714 41.84286) 3,412,983 Cigna Health Care: Pharmacy and Other Services Bloomfield Connecticut thecignagroup.com 72,400 247,100,000,000 David Cordani
15 23230 38 -77 8,304 POINT (-77.49153 37.587) 3,290,323 Altria Tobacco Richmond Virginia altria.com 6,200 20,400,000,000 William Gifford Jr.
16 95032 37 -122 27,682 POINT (-121.92359 37.20859) 2,785,714 Netflix Entertainment Los Gatos California netflix.com 14,000 39,000,000,000 Ted Sarandos
17 85251 33 -112 39,976 POINT (-111.92025 33.49406) 2,733,333 Taylor Morrison Home Homebuilders Scottsdale Arizona taylormorrison.com 3,000 8,200,000,000 Sheryl Palmer
18 10282 41 -74 5,960 POINT (-74.01495 40.71655) 2,729,032 Goldman Sachs Commercial Banks New York New York goldmansachs.com 46,500 126,900,000,000 David Solomon
19 95131 37 -122 30,745 POINT (-121.89793 37.38729) 2,631,579 Super Micro Computer Computers, Office Equipment San Jose California supermicro.com 5,700 15,000,000,000 Charles Liang
20 43215 40 -83 16,999 POINT (-83.01262 39.96633) 2,604,444 Nationwide Insurance: Property and Casualty (Mutual) Columbus Ohio nationwide.com 22,500 58,600,000,000 Kirt Walker
21 94538 38 -122 67,704 POINT (-121.96361 37.50653) 2,267,442 TD Synnex Wholesalers: Electronics and Office Equipment Fremont California tdsynnex.com 25,800 58,500,000,000 Patrick Zammit
22 94025 37 -122 40,230 POINT (-122.1829 37.45087) 2,219,973 Meta Internet Services and Retailing Menlo Park California meta.com 74,100 164,500,000,000 Mark Zuckerberg
23 94612 38 -122 17,663 POINT (-122.2662 37.80789) 2,114,035 Block Financial Data Services Oakland California block.xyz 11,400 24,100,000,000 Jack Dorsey
24 45014 39 -85 45,652 POINT (-84.5521 39.32822) 2,017,857 Cincinnati Financial Insurance: Property and Casualty (Stock) Fairfield Ohio cinfin.com 5,600 11,300,000,000 Stephen Spray
25 02210 42 -71 6,554 POINT (-71.03942 42.34815) 1,803,279 Vertex Pharmaceuticals Pharmaceuticals Boston Massachusetts vrtx.com 6,100 11,000,000,000 Reshma Kewalramani
26 55126 45 -93 27,484 POINT (-93.13581 45.08614) 1,800,000 Land O'Lakes Food Consumer Products Arden Hills Minnesota landolakesinc.com 9,000 16,200,000,000 Beth Ford
27 71730 33 -93 29,187 POINT (-92.63458 33.20303) 1,543,103 Murphy USA Specialty Retailers: Other El Dorado Arkansas murphyusa.com 11,600 17,900,000,000 Andrew Clyde
28 23238 38 -78 25,893 POINT (-77.64138 37.59595) 1,486,413 Performance Food Wholesalers: Food and Grocery Richmond Virginia pfgc.com 36,800 54,700,000,000 George Holm
29 33408 27 -80 18,766 POINT (-80.05677 26.84115) 1,476,190 NextEra Energy Utilities: Gas and Electric Juno Beach Florida nexteraenergy.com 16,800 24,800,000,000 John Ketchum
30 60061 42 -88 27,883 POINT (-87.96046 42.2334) 1,390,728 CDW Information Technology Services Vernon Hills Illinois cdw.com 15,100 21,000,000,000 Christine Leahy
31 10036 41 -74 30,589 POINT (-73.99064 40.75976) 1,353,414 Verizon Telecommunications New York New York verizon.com 99,600 134,800,000,000 Hans Vestberg
32 46804 41 -85 29,177 POINT (-85.23913 41.05421) 1,346,154 Steel Dynamics Metals Fort Wayne Indiana steeldynamics.com 13,000 17,500,000,000 Mark Millett
33 28211 35 -81 32,637 POINT (-80.79604 35.16816) 1,314,815 Sonic Automotive Automotive Retailing, Services Charlotte North Carolina sonicautomotive.com 10,800 14,200,000,000 David Bruton Smith
34 55347 45 -93 30,467 POINT (-93.46638 44.82931) 1,282,609 C.H. Robinson Worldwide Transportation and Logistics Eden Prairie Minnesota chrobinson.com 13,800 17,700,000,000 David Bozeman
35 92879 34 -118 48,756 POINT (-117.5357 33.87979) 1,250,000 Monster Beverage Beverages Corona California monsterbevcorp.com 6,000 7,500,000,000 Rodney Sacks
36 48674 44 -84 42,547 POINT (-84.23229 43.70732) 1,194,444 Dow Chemicals Midland Michigan dow.com 36,000 43,000,000,000 James Fitterling
37 48265 42 -83 4,503 POINT (-83.0456 42.3317) 1,156,790 General Motors Motor Vehicles & Parts Detroit Michigan gm.com 162,000 187,400,000,000 Mary Barra
38 98052 48 -122 79,074 POINT (-122.1203 47.68148) 1,075,000 Microsoft Computer Software Redmond Washington microsoft.com 228,000 245,100,000,000 Satya Nadella
39 61265 41 -90 43,851 POINT (-90.48895 41.48195) 931,532 Deere Construction and Farm Machinery Moline Illinois deere.com 55,500 51,700,000,000 John May
40 45202 39 -85 17,022 POINT (-84.50243 39.10885) 777,778 Procter & Gamble Household and Personal Products Cincinnati Ohio pginvestor.com 108,000 84,000,000,000 Jon Moeller
41 98027 48 -122 28,335 POINT (-122.00176 47.50387) 764,264 Costco General Merchandisers Issaquah Washington costco.com 333,000 254,500,000,000 Ron Vachris
42 80021 40 -105 35,562 POINT (-105.11448 39.89105) 756,250 Ball Packaging, Containers Westminster Colorado ball.com 16,000 12,100,000,000 Daniel Fisher
43 68179 41 -96 0 POINT (-95.9352 41.2597) 746,914 Union Pacific Railroads Omaha Nebraska up.com 32,400 24,200,000,000 Jim Vena
44 45215 39 -84 30,806 POINT (-84.46221 39.23536) 730,189 General Electric Aerospace & Defense Evendale Ohio ge.com 53,000 38,700,000,000 Lawrence Culp Jr.
45 53212 43 -88 29,099 POINT (-87.90845 43.07464) 670,412 Manpower Diversified Outsourcing Services Milwaukee Wisconsin manpowergroup.com 26,700 17,900,000,000 Jonas Prising
46 97005 45 -123 27,812 POINT (-122.80397 45.49144) 647,355 Nike Apparel Beaverton Oregon nike.com 79,400 51,400,000,000 Elliott Hill
47 35242 33 -87 56,956 POINT (-86.67073 33.42371) 616,667 Vulcan Materials Building Materials, Glass Birmingham Alabama vulcanmaterials.com 12,000 7,400,000,000 Thomas Hill
48 75039 33 -97 22,450 POINT (-96.94042 32.88592) 605,948 Fluor Engineering & Construction Irving Texas fluor.com 26,900 16,300,000,000 James Breuer
49 30354 34 -84 15,487 POINT (-84.38609 33.66058) 598,058 Delta Airlines Airlines Atlanta Georgia delta.com 103,000 61,600,000,000 Edward Bastian
50 95134 37 -122 30,255 POINT (-121.94528 37.43003) 595,133 Cisco Systems Network and Other Communications Equipment San Jose California cisco.com 90,400 53,800,000,000 Charles Robbins
51 60015 42 -88 27,720 POINT (-87.87486 42.17239) 584,950 Walgreens Food & Drug Stores Deerfield Illinois walgreensbootsalliance.com 252,500 147,700,000,000 Timothy Wentworth
52 94086 37 -122 48,956 POINT (-122.02316 37.37164) 538,462 Intuitive Surgical Medical Products and Equipment Sunnyvale California intuitive.com 15,600 8,400,000,000 Gary Guthart
53 33418 27 -80 42,979 POINT (-80.16641 26.86077) 516,667 Carrier Global Industrial Machinery Palm Beach Gardens Florida carrier.com 48,000 24,800,000,000 David Gitlin
54 77079 30 -96 35,540 POINT (-95.6037 29.77632) 487,719 Baker Hughes Oil and Gas Equipment, Services Houston Texas bakerhughes.com 57,000 27,800,000,000 Lorenzo Simonelli
55 48152 42 -83 30,394 POINT (-83.37433 42.42597) 433,333 Masco Home Equipment, Furnishings Livonia Michigan masco.com 18,000 7,800,000,000 Keith Allman
56 10036 41 -74 30,589 POINT (-73.99064 40.75976) 422,594 News Corp. Publishing, Printing New York New York newscorp.com 23,900 10,100,000,000 Robert Thomson
57 85054 34 -112 10,159 POINT (-111.94763 33.67515) 380,952 Republic Services Waste Management Phoenix Arizona republicservices.com 42,000 16,000,000,000 Jon Vander Ark
58 49022 42 -86 29,796 POINT (-86.3675 42.11434) 377,273 Whirlpool Electronics, Electrical Equip. Benton Harbor Michigan whirlpoolcorp.com 44,000 16,600,000,000 Marc Bitzer
59 72745 36 -94 14,521 POINT (-94.10046 36.2477) 360,119 J.B. Hunt Transport Services Trucking, Truck Leasing Lowell Arkansas jbhunt.com 33,600 12,100,000,000 Shelley Simpson
60 02451 42 -71 18,153 POINT (-71.2573 42.39859) 343,200 Thermo Fisher Scientific Scientific, Photographic and Control Equipment Waltham Massachusetts thermofisher.com 125,000 42,900,000,000 Marc Casper
61 89113 36 -115 37,313 POINT (-115.26236 36.06017) 281,796 Las Vegas Sands Hotels, Casinos, Resorts Las Vegas Nevada sands.com 40,100 11,300,000,000 Robert Goldstein
62 98390 47 -122 11,497 POINT (-122.22894 47.21195) 271,795 Lululemon athletica Specialty Retailers: Apparel Sumner Washington lululemon.com 39,000 10,600,000,000 Calvin McDonald
63 37203 36 -87 20,234 POINT (-86.78986 36.14937) 260,517 HCA Healthcare Health Care: Medical Facilities Nashville Tennessee hcahealthcare.com 271,000 70,600,000,000 Samuel Hazen
64 30328 34 -84 38,821 POINT (-84.38617 33.93194) 244,761 UPS Mail, Package and Freight Delivery Atlanta Georgia ups.com 372,200 91,100,000,000 Carol Tomé
65 40213 38 -86 15,805 POINT (-85.71571 38.177) 236,593 Yum Brands Food Services Louisville Kentucky yum.com 31,700 7,500,000,000 David Gibbs
66 10017 41 -74 14,985 POINT (-73.9726 40.75235) 209,613 Omnicom Advertising, Marketing New York New York omnicomgroup.com 74,900 15,700,000,000 John Wren
In [121]:
minsmaxeffco = gdfstsinsmaxeffco.explore(column='Efficiency', name='The Most Efficient Company in each Industry visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactinsmaxeffco.explore(m=minsmaxeffco, column='Efficiency', name='The Most Efficient Company in each Industry visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(minsmaxeffco)
minsmaxeffco
Out[121]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [122]:
# Check the Most Efficient Industry in each State.
# We use PARTITION BY-like feature to grouping but not making any new Index.
pd.set_option('display.max_rows',None)
dfstmaxeffin = df.iloc[0:1]

for st in stslist[0:]:
    dftemp = df.where(df['State'] == st[0]).dropna()
    dftemp.insert(6,'Efficiency',1)
    dftemp['Efficiency'] = dftemp['Revenue (rounded)'] / dftemp['Employees']
    dfstmaxeffin = pd.concat([dfstmaxeffin, dftemp.groupby(['State','Industry'], as_index=False).sum('Efficiency').sort_values('Efficiency', ascending=False).head(1)])

dfstmaxeffin = dfstmaxeffin.iloc[1:]
dfstmaxeffin = dfstmaxeffin[['State','Industry','Efficiency']].sort_values(by=['Efficiency'], ascending=False).reset_index(drop=True)
dfstmaxeffin10 = dfstmaxeffin.head(10)
dfstmaxeffin
Out[122]:
State Industry Efficiency
0 Texas Petroleum Refining 43,606,030
1 New York Diversified Financials 28,300,270
2 California Wholesalers: Diversified 19,400,000
3 District of Columbia Diversified Financials 18,621,951
4 Virginia Diversified Financials 15,074,074
5 Ohio Real Estate 11,428,571
6 Florida Energy 8,978,723
7 New Jersey Petroleum Refining 8,487,179
8 Oklahoma Mining, Crude-Oil Production 6,913,043
9 Pennsylvania Wholesalers: Health Care 6,681,818
10 Colorado Mining, Crude-Oil Production 6,592,342
11 Tennessee Petroleum Refining 6,250,000
12 Missouri Insurance: Life, Health (Stock) 5,390,244
13 Wisconsin Insurance: Life, Health (Mutual) 5,048,780
14 Massachusetts Energy 4,980,743
15 Minnesota Food Production 3,672,897
16 Connecticut Health Care: Pharmacy and Other Services 3,412,983
17 Michigan Motor Vehicles & Parts 2,907,881
18 Arizona Homebuilders 2,733,333
19 Illinois Food Production 2,639,881
20 Georgia Homebuilders 2,632,353
21 North Carolina Commercial Banks 2,450,342
22 Nebraska Insurance: Life, Health (Mutual) 2,246,154
23 Rhode Island Insurance: Property and Casualty (Stock) 1,793,103
24 Kentucky Health Care: Insurance and Managed Care 1,792,998
25 Indiana Health Care: Insurance and Managed Care 1,706,847
26 Maryland Energy 1,661,972
27 Washington Internet Services and Retailing 1,559,276
28 Arkansas Specialty Retailers: Other 1,543,103
29 Oregon Automotive Retailing, Services 1,211,921
30 Louisiana Utilities: Gas and Electric 967,480
31 Iowa Insurance: Life, Health (Stock) 817,259
32 Nevada Hotels, Casinos, Resorts 757,071
33 Kansas Food Production 650,000
34 Alabama Building Materials, Glass 616,667
35 Idaho Semiconductors and Other Electronic Components 522,917
36 Delaware Chemicals 516,667
In [123]:
dfstmaxeffin10 = dfstmaxeffin10.merge(df[['State','Company','Industry','Zip Code']], how = 'inner', on = ['State','Industry'])
dfstmaxeffin10[['State','Industry','Company','Zip Code','Efficiency']].sort_values('Efficiency', ascending=False).reset_index(drop=True)
Out[123]:
State Industry Company Zip Code Efficiency
0 Texas Petroleum Refining Exxon Mobil 77389 43,606,030
1 Texas Petroleum Refining Phillips 66 77042 43,606,030
2 Texas Petroleum Refining Valero Energy 78249 43,606,030
3 Texas Petroleum Refining HF Sinclair 75219 43,606,030
4 Texas Petroleum Refining Par Pacific 77024 43,606,030
5 Texas Petroleum Refining Chevron 77002 43,606,030
6 New York Diversified Financials Blackstone 10154 28,300,270
7 New York Diversified Financials Voya Financial 10169 28,300,270
8 New York Diversified Financials Jefferies Financial 10022 28,300,270
9 New York Diversified Financials Marsh & McLennan 10036 28,300,270
10 New York Diversified Financials American Express 10285 28,300,270
11 New York Diversified Financials StoneX 10169 28,300,270
12 California Wholesalers: Diversified A-Mark Precious Metals 90245 19,400,000
13 District of Columbia Diversified Financials Fannie Mae 20005 18,621,951
14 Virginia Diversified Financials Freddie Mac 22102 15,074,074
15 Ohio Real Estate Welltower 43615 11,428,571
16 Florida Energy World Kinect 33178 8,978,723
17 New Jersey Petroleum Refining PBF Energy 07054 8,487,179
18 Oklahoma Mining, Crude-Oil Production Devon Energy 73102 6,913,043
19 Pennsylvania Wholesalers: Health Care Cencora 19428 6,681,818
In [124]:
gdfstsstmaxeffin10 = gdfsts.merge(dfstmaxeffin10, how = 'inner', on = ['State'])
gdfusactstmaxeffin10 = gdfusact.merge(dfstmaxeffin10, how = 'inner', on = ['Zip Code']).sort_values('Efficiency', ascending=False).reset_index(drop=True)
gdfusactstmaxeffin10
Out[124]:
Zip Code Latitude Longitude Population geometry State Industry Efficiency Company
0 77042 30 -96 40,725 POINT (-95.56015 29.74125) Texas Petroleum Refining 43,606,030 Phillips 66
1 78249 30 -99 61,772 POINT (-98.614 29.56752) Texas Petroleum Refining 43,606,030 Valero Energy
2 77389 30 -96 44,545 POINT (-95.50752 30.11509) Texas Petroleum Refining 43,606,030 Exxon Mobil
3 75219 33 -97 25,001 POINT (-96.81315 32.81087) Texas Petroleum Refining 43,606,030 HF Sinclair
4 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas Petroleum Refining 43,606,030 Chevron
5 77024 30 -96 37,647 POINT (-95.50869 29.77073) Texas Petroleum Refining 43,606,030 Par Pacific
6 10285 41 -74 0 POINT (-74.01492 40.71201) New York Diversified Financials 28,300,270 American Express
7 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York Diversified Financials 28,300,270 Marsh & McLennan
8 10154 41 -74 0 POINT (-73.97249 40.75778) New York Diversified Financials 28,300,270 Blackstone
9 10169 41 -74 0 POINT (-73.97643 40.75467) New York Diversified Financials 28,300,270 StoneX
10 10169 41 -74 0 POINT (-73.97643 40.75467) New York Diversified Financials 28,300,270 Voya Financial
11 10022 41 -74 34,340 POINT (-73.96787 40.75856) New York Diversified Financials 28,300,270 Jefferies Financial
12 90245 34 -118 16,863 POINT (-118.40161 33.91709) California Wholesalers: Diversified 19,400,000 A-Mark Precious Metals
13 20005 39 -77 12,960 POINT (-77.0316 38.90443) District of Columbia Diversified Financials 18,621,951 Fannie Mae
14 22102 39 -77 28,577 POINT (-77.22901 38.95199) Virginia Diversified Financials 15,074,074 Freddie Mac
15 43615 42 -84 40,813 POINT (-83.67255 41.65045) Ohio Real Estate 11,428,571 Welltower
16 33178 26 -80 65,515 POINT (-80.4213 25.83578) Florida Energy 8,978,723 World Kinect
17 07054 41 -74 30,139 POINT (-74.40239 40.85527) New Jersey Petroleum Refining 8,487,179 PBF Energy
18 73102 35 -98 3,590 POINT (-97.5191 35.47065) Oklahoma Mining, Crude-Oil Production 6,913,043 Devon Energy
19 19428 40 -75 20,225 POINT (-75.30317 40.08011) Pennsylvania Wholesalers: Health Care 6,681,818 Cencora
In [125]:
mstmaxeffin = gdfstsstmaxeffin10.explore(column='Efficiency', name='The Most Efficient Industry in each State visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactstmaxeffin10.explore(m=mstmaxeffin, column='Efficiency', name='The Most Efficient Industry in each State visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mstmaxeffin)
mstmaxeffin
Out[125]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
# Conclusion:
# 1. Even though California is known with its Silicon Valley and movie Industry, but the Most Efficient one is not one of them. It's Wholesalers: Diversified.
# 2. Even though New York state has many companies in Commercial Banks Industry, turns out the Most Efficient one is Diversified Financials.
# 3. Many energy-related Companies are identified as the Most Efficient Industry.
In [126]:
# Check the Least Efficient Industry in each State.
# We use PARTITION BY-like feature to grouping but not making any new Index.
pd.set_option('display.max_rows',None)
dfstmineffin = df.iloc[0:1]

for st in stslist[0:]:
    dftemp = df.where(df['State'] == st[0]).dropna()
    dftemp.insert(6,'Efficiency',1)
    dftemp['Efficiency'] = dftemp['Revenue (rounded)'] / dftemp['Employees']
    dfstmineffin = pd.concat([dfstmineffin, dftemp.groupby(['State','Industry'], as_index=False).sum('Efficiency').sort_values('Efficiency', ascending=True).head(1)])

dfstmineffin = dfstmineffin.iloc[1:]
dfstmineffin = dfstmineffin[['State','Industry','Efficiency']].sort_values(by=['Efficiency'], ascending=False).reset_index(drop=True)
dfstmineffin10 = dfstmineffin.head(10)
dfstmineffin
Out[126]:
State Industry Efficiency
0 Oklahoma Pipelines 5,983,422
1 Nevada Hotels, Casinos, Resorts 757,071
2 Kansas Food Production 650,000
3 Oregon Apparel 647,355
4 Nebraska Engineering & Construction 528,302
5 Louisiana Telecommunications 524,000
6 Delaware Chemicals 516,667
7 Alabama Commercial Banks 479,592
8 Iowa Specialty Retailers: Other 450,151
9 Rhode Island Aerospace & Defense 402,941
10 Idaho Food & Drug Stores 402,848
11 Michigan Electronics, Electrical Equip. 377,273
12 District of Columbia Industrial Machinery 373,913
13 North Carolina Health Care: Pharmacy and Other Services 373,777
14 Arkansas General Merchandisers 324,286
15 Indiana Packaging, Containers 292,857
16 Wisconsin General Merchandisers 270,000
17 Georgia Mail, Package and Freight Delivery 244,761
18 Minnesota General Merchandisers 242,273
19 Kentucky Food Services 236,593
20 Arizona Food & Drug Stores 220,000
21 Tennessee Mail, Package and Freight Delivery 207,771
22 Ohio Diversified Outsourcing Services 206,452
23 Missouri Specialty Retailers: Other 195,093
24 Illinois Food Services 172,667
25 Colorado Health Care: Medical Facilities 168,421
26 Maryland Hotels, Casinos, Resorts 161,935
27 Massachusetts Specialty Retailers: Apparel 154,945
28 Connecticut Network and Other Communications Equipment 121,600
29 Washington Food Services 100,277
30 New York Diversified Outsourcing Services 71,795
31 Pennsylvania Diversified Outsourcing Services 65,242
32 Virginia Hotels, Casinos, Resorts 61,878
33 Florida Food Services 59,655
34 New Jersey Information Technology Services 58,492
35 Texas Food Services 46,029
36 California Information Technology Services 21,333
In [ ]:
# Conclusion:
# 1. Walmart as the Biggest Revenue Company and the Biggest Employer Company in State category, turns out, in terms of Efficiency, 
#    becomes one of the least.
# 2. Information Technology Services is the Lowest Efficient Industry. It's intriguing due to selling services is not the same as selling hardwares or softwares.
#    It just needs skills, knowledges, and experiences. 😕
In [127]:
dfstmineffin10 = dfstmineffin10.merge(df[['State','Company','Industry','Zip Code']], how = 'inner', on = ['State','Industry'])
dfstmineffin10[['State','Industry','Company','Zip Code','Efficiency']].sort_values('Efficiency', ascending=False).reset_index(drop=True)
Out[127]:
State Industry Company Zip Code Efficiency
0 Oklahoma Pipelines Oneok 74103 5,983,422
1 Oklahoma Pipelines Williams 74172 5,983,422
2 Nevada Hotels, Casinos, Resorts MGM Resorts International 89109 757,071
3 Nevada Hotels, Casinos, Resorts Las Vegas Sands 89113 757,071
4 Nevada Hotels, Casinos, Resorts Caesars Entertainment 89501 757,071
5 Kansas Food Production Seaboard 66202 650,000
6 Oregon Apparel Nike 97005 647,355
7 Nebraska Engineering & Construction Peter Kiewit Sons' 68102 528,302
8 Louisiana Telecommunications Lumen Technologies 71203 524,000
9 Delaware Chemicals DuPont 19805 516,667
10 Alabama Commercial Banks Regions Financial 35203 479,592
11 Iowa Specialty Retailers: Other Casey's General Stores 50021 450,151
12 Rhode Island Aerospace & Defense Textron 02903 402,941
In [128]:
gdfstsstmineffin10 = gdfsts.merge(dfstmineffin10, how = 'inner', on = ['State'])
gdfusactstmineffin10 = gdfusact.merge(dfstmineffin10, how = 'inner', on = ['Zip Code']).sort_values('Efficiency', ascending=False).reset_index(drop=True)
gdfusactstmineffin10
Out[128]:
Zip Code Latitude Longitude Population geometry State Industry Efficiency Company
0 74103 36 -96 2,419 POINT (-95.9957 36.15617) Oklahoma Pipelines 5,983,422 Oneok
1 74172 36 -96 0 POINT (-95.9905 36.1544) Oklahoma Pipelines 5,983,422 Williams
2 89109 36 -115 6,924 POINT (-115.16327 36.12603) Nevada Hotels, Casinos, Resorts 757,071 MGM Resorts International
3 89113 36 -115 37,313 POINT (-115.26236 36.06017) Nevada Hotels, Casinos, Resorts 757,071 Las Vegas Sands
4 89501 40 -120 3,641 POINT (-119.81262 39.52602) Nevada Hotels, Casinos, Resorts 757,071 Caesars Entertainment
5 66202 39 -95 17,321 POINT (-94.66909 39.02392) Kansas Food Production 650,000 Seaboard
6 97005 45 -123 27,812 POINT (-122.80397 45.49144) Oregon Apparel 647,355 Nike
7 68102 41 -96 9,311 POINT (-95.93224 41.26231) Nebraska Engineering & Construction 528,302 Peter Kiewit Sons'
8 71203 33 -92 38,770 POINT (-92.01351 32.58398) Louisiana Telecommunications 524,000 Lumen Technologies
9 19805 40 -76 40,315 POINT (-75.59373 39.74523) Delaware Chemicals 516,667 DuPont
10 35203 34 -87 3,301 POINT (-86.80999 33.51847) Alabama Commercial Banks 479,592 Regions Financial
11 50021 42 -94 29,718 POINT (-93.56838 41.7207) Iowa Specialty Retailers: Other 450,151 Casey's General Stores
12 02903 42 -71 12,309 POINT (-71.41003 41.81902) Rhode Island Aerospace & Defense 402,941 Textron
In [129]:
mstmineffin10 = gdfstsstmineffin10.explore(column='Efficiency', name='The Least Efficient Industry in each State visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactstmineffin10.explore(m=mstmineffin10, column='Efficiency', name='The Least Efficient Industry in each State visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(mstmineffin10)
mstmineffin10
Out[129]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [130]:
# The Most Efficient Industry in US
dfusmaxeffin = df.groupby(['Industry'], as_index=False).sum('Employees')
dfusmaxeffin.insert(3,'Efficiency',1)
dfusmaxeffin['Efficiency'] = dfusmaxeffin['Revenue (rounded)'] / dfusmaxeffin['Employees']
dfusmaxeffin = dfusmaxeffin.sort_values('Efficiency', ascending=False).reset_index(drop=True)[['Industry','Employees','Revenue (rounded)','Efficiency']]
dfusmaxeffin
Out[130]:
Industry Employees Revenue (rounded) Efficiency
0 Petroleum Refining 160600 1,044,500,000,000 6,503,736
1 Pipelines 55200 268,400,000,000 4,862,319
2 Wholesalers: Health Care 188600 853,200,000,000 4,523,860
3 Insurance: Life, Health (Mutual) 70800 249,800,000,000 3,528,249
4 Homebuilders 49800 119,800,000,000 2,405,622
5 Mining, Crude-Oil Production 89000 210,700,000,000 2,367,416
6 Insurance: Property and Casualty (Mutual) 113800 226,100,000,000 1,986,819
7 Diversified Financials 350100 627,600,000,000 1,792,631
8 Wholesalers: Electronics and Office Equipment 88900 158,200,000,000 1,779,528
9 Insurance: Life, Health (Stock) 178200 299,200,000,000 1,679,012
10 Health Care: Insurance and Managed Care 650300 908,000,000,000 1,396,279
11 Energy 121900 163,200,000,000 1,338,802
12 Computers, Office Equipment 447700 598,300,000,000 1,336,386
13 Health Care: Pharmacy and Other Services 572800 669,500,000,000 1,168,820
14 Wholesalers: Food and Grocery 186100 211,900,000,000 1,138,635
15 Utilities: Gas and Electric 306200 329,200,000,000 1,075,114
16 Insurance: Property and Casualty (Stock) 789100 842,900,000,000 1,068,179
17 Securities 172200 175,900,000,000 1,021,487
18 Automotive Retailing, Services 232000 215,700,000,000 929,741
19 Food Production 241400 222,800,000,000 922,949
20 Pharmaceuticals 549400 487,300,000,000 886,968
21 Commercial Banks 1577000 1,321,000,000,000 837,666
22 Telecommunications 566700 473,800,000,000 836,068
23 Metals 140900 116,600,000,000 827,537
24 Entertainment 338000 259,900,000,000 768,935
25 Semiconductors and Other Electronic Components 627900 446,900,000,000 711,738
26 Beverages 131200 91,600,000,000 698,171
27 Computer Software 565200 393,200,000,000 695,683
28 Financial Data Services 260100 175,300,000,000 673,972
29 Railroads 75500 50,800,000,000 672,848
30 Wholesalers: Diversified 255100 169,600,000,000 664,837
31 Motor Vehicles & Parts 893000 590,800,000,000 661,590
32 Construction and Farm Machinery 210900 138,900,000,000 658,606
33 Tobacco 89300 58,300,000,000 652,856
34 Internet Services and Retailing 2071800 1,330,100,000,000 642,002
35 Household and Personal Products 255000 155,300,000,000 609,020
36 Apparel 140500 79,600,000,000 566,548
37 Chemicals 379700 203,000,000,000 534,633
38 Building Materials, Glass 66000 34,800,000,000 527,273
39 Airlines 467900 221,400,000,000 473,178
40 Aerospace & Defense 911500 407,400,000,000 446,956
41 Food Consumer Products 604700 263,800,000,000 436,249
42 Oil and Gas Equipment, Services 139000 59,600,000,000 428,777
43 Publishing, Printing 23900 10,100,000,000 422,594
44 Packaging, Containers 191400 80,800,000,000 422,153
45 Engineering & Construction 240500 100,000,000,000 415,800
46 Food & Drug Stores 1148100 441,900,000,000 384,897
47 Medical Products and Equipment 501600 184,600,000,000 368,022
48 Waste Management 103700 38,100,000,000 367,406
49 Trucking, Truck Leasing 33600 12,100,000,000 360,119
50 General Merchandisers 3101200 1,116,800,000,000 360,119
51 Industrial Machinery 594700 207,800,000,000 349,420
52 Network and Other Communications Equipment 251700 87,800,000,000 348,828
53 Real Estate 273800 95,100,000,000 347,334
54 Scientific, Photographic and Control Equipment 125000 42,900,000,000 343,200
55 Specialty Retailers: Other 1558200 505,200,000,000 324,220
56 Home Equipment, Furnishings 83600 26,200,000,000 313,397
57 Electronics, Electrical Equip. 158300 46,000,000,000 290,587
58 Transportation and Logistics 251400 60,700,000,000 241,448
59 Health Care: Medical Facilities 573200 132,500,000,000 231,158
60 Mail, Package and Freight Delivery 794300 178,800,000,000 225,104
61 Advertising, Marketing 128200 26,400,000,000 205,928
62 Specialty Retailers: Apparel 669500 121,800,000,000 181,927
63 Diversified Outsourcing Services 564900 89,500,000,000 158,435
64 Hotels, Casinos, Resorts 495100 76,100,000,000 153,706
65 Information Technology Services 1478900 201,900,000,000 136,520
66 Food Services 1109800 103,600,000,000 93,350
In [ ]:
# Conclusion: Energy-related, Health Care, Insurance, and Construction are the Most Efficient Industries in US.
In [131]:
# Draw the 10 Most Efficient Industries in US
dfusmaxeffin10 = dfusmaxeffin.head(10)

dfusmaxeffin10 = dfusmaxeffin10.merge(df[['State','Company','Industry','Zip Code']], how = 'inner', on = ['Industry'])
dfusmaxeffin10[['State','Industry','Company','Zip Code','Efficiency']].sort_values('Efficiency', ascending=False).reset_index(drop=True)

gdfstsusmaxeffin10 = gdfsts.merge(dfusmaxeffin10, how = 'inner', on = ['State'])
gdfusactusmaxeffin10 = gdfusact.merge(dfusmaxeffin10, how = 'inner', on = ['Zip Code']).sort_values('Efficiency', ascending=False).reset_index(drop=True)
gdfusactusmaxeffin10
Out[131]:
Zip Code Latitude Longitude Population geometry Industry Employees Revenue (rounded) Efficiency State Company
0 37027 36 -87 61,961 POINT (-86.78439 35.99978) Petroleum Refining 160600 1,044,500,000,000 6,503,736 Tennessee Delek US
1 77002 30 -95 19,616 POINT (-95.36538 29.75635) Petroleum Refining 160600 1,044,500,000,000 6,503,736 Texas Chevron
2 78249 30 -99 61,772 POINT (-98.614 29.56752) Petroleum Refining 160600 1,044,500,000,000 6,503,736 Texas Valero Energy
3 77389 30 -96 44,545 POINT (-95.50752 30.11509) Petroleum Refining 160600 1,044,500,000,000 6,503,736 Texas Exxon Mobil
4 77042 30 -96 40,725 POINT (-95.56015 29.74125) Petroleum Refining 160600 1,044,500,000,000 6,503,736 Texas Phillips 66
5 77024 30 -96 37,647 POINT (-95.50869 29.77073) Petroleum Refining 160600 1,044,500,000,000 6,503,736 Texas Par Pacific
6 45840 41 -84 54,342 POINT (-83.64943 41.02626) Petroleum Refining 160600 1,044,500,000,000 6,503,736 Ohio Marathon Petroleum
7 07054 41 -74 30,139 POINT (-74.40239 40.85527) Petroleum Refining 160600 1,044,500,000,000 6,503,736 New Jersey PBF Energy
8 75219 33 -97 25,001 POINT (-96.81315 32.81087) Petroleum Refining 160600 1,044,500,000,000 6,503,736 Texas HF Sinclair
9 74103 36 -96 2,419 POINT (-95.9957 36.15617) Pipelines 55200 268,400,000,000 4,862,319 Oklahoma Oneok
10 75225 33 -97 22,383 POINT (-96.79109 32.86511) Pipelines 55200 268,400,000,000 4,862,319 Texas Energy Transfer
11 74172 36 -96 0 POINT (-95.9905 36.1544) Pipelines 55200 268,400,000,000 4,862,319 Oklahoma Williams
12 77002 30 -95 19,616 POINT (-95.36538 29.75635) Pipelines 55200 268,400,000,000 4,862,319 Texas Enterprise Products Partners
13 77002 30 -95 19,616 POINT (-95.36538 29.75635) Pipelines 55200 268,400,000,000 4,862,319 Texas Targa Resources
14 77002 30 -95 19,616 POINT (-95.36538 29.75635) Pipelines 55200 268,400,000,000 4,862,319 Texas Cheniere Energy
15 77002 30 -95 19,616 POINT (-95.36538 29.75635) Pipelines 55200 268,400,000,000 4,862,319 Texas Kinder Morgan
16 77002 30 -95 19,616 POINT (-95.36538 29.75635) Pipelines 55200 268,400,000,000 4,862,319 Texas Plains GP
17 23060 38 -78 36,111 POINT (-77.53427 37.65981) Wholesalers: Health Care 188600 853,200,000,000 4,523,860 Virginia Owens & Minor
18 43017 40 -83 41,422 POINT (-83.13314 40.1189) Wholesalers: Health Care 188600 853,200,000,000 4,523,860 Ohio Cardinal Health
19 75039 33 -97 22,450 POINT (-96.94042 32.88592) Wholesalers: Health Care 188600 853,200,000,000 4,523,860 Texas McKesson
20 11747 41 -73 19,826 POINT (-73.40931 40.78372) Wholesalers: Health Care 188600 853,200,000,000 4,523,860 New York Henry Schein
21 19428 40 -75 20,225 POINT (-75.30317 40.08011) Wholesalers: Health Care 188600 853,200,000,000 4,523,860 Pennsylvania Cencora
22 53202 43 -88 26,269 POINT (-87.89893 43.04561) Insurance: Life, Health (Mutual) 70800 249,800,000,000 3,528,249 Wisconsin Northwestern Mutual
23 10001 41 -74 29,079 POINT (-73.99728 40.75064) Insurance: Life, Health (Mutual) 70800 249,800,000,000 3,528,249 New York Guardian Life
24 68175 41 -96 0 POINT (-95.96584 41.26502) Insurance: Life, Health (Mutual) 70800 249,800,000,000 3,528,249 Nebraska Mutual of Omaha Insurance
25 01111 42 -73 0 POINT (-72.54793 42.11733) Insurance: Life, Health (Mutual) 70800 249,800,000,000 3,528,249 Massachusetts Mass Mutual
26 10017 41 -74 14,985 POINT (-73.9726 40.75235) Insurance: Life, Health (Mutual) 70800 249,800,000,000 3,528,249 New York TIAA
27 45202 39 -85 17,022 POINT (-84.50243 39.10885) Insurance: Life, Health (Mutual) 70800 249,800,000,000 3,528,249 Ohio Western & Southern Financial
28 10010 41 -74 31,905 POINT (-73.98243 40.73899) Insurance: Life, Health (Mutual) 70800 249,800,000,000 3,528,249 New York New York Life Insurance
29 55415 45 -93 6,474 POINT (-93.2578 44.97463) Insurance: Life, Health (Mutual) 70800 249,800,000,000 3,528,249 Minnesota Thrivent Financial for Lutherans
30 19034 40 -75 7,084 POINT (-75.20953 40.13353) Homebuilders 49800 119,800,000,000 2,405,622 Pennsylvania Toll Brothers
31 30326 34 -84 8,497 POINT (-84.36342 33.84957) Homebuilders 49800 119,800,000,000 2,405,622 Georgia Pulte
32 20190 39 -77 22,092 POINT (-77.33806 38.95968) Homebuilders 49800 119,800,000,000 2,405,622 Virginia NVR
33 85251 33 -112 39,976 POINT (-111.92025 33.49406) Homebuilders 49800 119,800,000,000 2,405,622 Arizona Taylor Morrison Home
34 33126 26 -80 47,038 POINT (-80.30054 25.78061) Homebuilders 49800 119,800,000,000 2,405,622 Florida Lennar
35 76011 33 -97 22,297 POINT (-97.08223 32.7543) Homebuilders 49800 119,800,000,000 2,405,622 Texas D.R. Horton
36 10036 41 -74 30,589 POINT (-73.99064 40.75976) Mining, Crude-Oil Production 89000 210,700,000,000 2,367,416 New York Hess
37 79701 32 -102 27,678 POINT (-102.08105 31.99239) Mining, Crude-Oil Production 89000 210,700,000,000 2,367,416 Texas Diamondback Energy
38 80202 40 -105 18,233 POINT (-104.99768 39.75156) Mining, Crude-Oil Production 89000 210,700,000,000 2,367,416 Colorado Ovintiv
39 77079 30 -96 35,540 POINT (-95.6037 29.77632) Mining, Crude-Oil Production 89000 210,700,000,000 2,367,416 Texas ConocoPhillips
40 77046 30 -95 1,873 POINT (-95.43301 29.73438) Mining, Crude-Oil Production 89000 210,700,000,000 2,367,416 Texas Occidental Petroleum
41 77042 30 -96 40,725 POINT (-95.56015 29.74125) Mining, Crude-Oil Production 89000 210,700,000,000 2,367,416 Texas APA
42 80237 40 -105 22,764 POINT (-104.90178 39.63996) Mining, Crude-Oil Production 89000 210,700,000,000 2,367,416 Colorado Newmont
43 85004 33 -112 11,178 POINT (-112.06988 33.45159) Mining, Crude-Oil Production 89000 210,700,000,000 2,367,416 Arizona Freeport-McMoRan
44 77002 30 -95 19,616 POINT (-95.36538 29.75635) Mining, Crude-Oil Production 89000 210,700,000,000 2,367,416 Texas EOG Resources
45 73102 35 -98 3,590 POINT (-97.5191 35.47065) Mining, Crude-Oil Production 89000 210,700,000,000 2,367,416 Oklahoma Devon Energy
46 43215 40 -83 16,999 POINT (-83.01262 39.96633) Insurance: Property and Casualty (Mutual) 113800 226,100,000,000 1,986,819 Ohio Nationwide
47 48917 43 -85 32,029 POINT (-84.63897 42.72509) Insurance: Property and Casualty (Mutual) 113800 226,100,000,000 1,986,819 Michigan Auto-Owners Insurance
48 61710 41 -89 79,633 POINT (-88.9894 40.516) Insurance: Property and Casualty (Mutual) 113800 226,100,000,000 1,986,819 Illinois State Farm
49 16530 42 -80 94,831 POINT (-80.08204 42.13039) Insurance: Property and Casualty (Mutual) 113800 226,100,000,000 1,986,819 Pennsylvania Erie Insurance
50 91367 34 -119 45,427 POINT (-118.61518 34.17708) Insurance: Property and Casualty (Mutual) 113800 226,100,000,000 1,986,819 California Farmers Insurance Exchange
51 33160 26 -80 43,225 POINT (-80.13583 25.93234) Diversified Financials 350100 627,600,000,000 1,792,631 Florida Icahn Enterprises
52 55474 45 -93 28,071 POINT (-93.27 44.98) Diversified Financials 350100 627,600,000,000 1,792,631 Minnesota Ameriprise Financial
53 10285 41 -74 0 POINT (-74.01492 40.71201) Diversified Financials 350100 627,600,000,000 1,792,631 New York American Express
54 22102 39 -77 28,577 POINT (-77.22901 38.95199) Diversified Financials 350100 627,600,000,000 1,792,631 Virginia Freddie Mac
55 10154 41 -74 0 POINT (-73.97249 40.75778) Diversified Financials 350100 627,600,000,000 1,792,631 New York Blackstone
56 20005 39 -77 12,960 POINT (-77.0316 38.90443) Diversified Financials 350100 627,600,000,000 1,792,631 District of Columbia Fannie Mae
57 48226 42 -83 6,893 POINT (-83.05034 42.33182) Diversified Financials 350100 627,600,000,000 1,792,631 Michigan Ally Financial
58 10169 41 -74 0 POINT (-73.97643 40.75467) Diversified Financials 350100 627,600,000,000 1,792,631 New York StoneX
59 06902 41 -74 72,915 POINT (-73.54751 41.05949) Diversified Financials 350100 627,600,000,000 1,792,631 Connecticut Synchrony Financial
60 77019 30 -95 23,662 POINT (-95.41212 29.75318) Diversified Financials 350100 627,600,000,000 1,792,631 Texas Corebridge Financial
61 10036 41 -74 30,589 POINT (-73.99064 40.75976) Diversified Financials 350100 627,600,000,000 1,792,631 New York Marsh & McLennan
62 60008 42 -88 22,949 POINT (-88.0229 42.0739) Diversified Financials 350100 627,600,000,000 1,792,631 Illinois Arthur J. Gallagher
63 60015 42 -88 27,720 POINT (-87.87486 42.17239) Diversified Financials 350100 627,600,000,000 1,792,631 Illinois Discover Financial
64 10169 41 -74 0 POINT (-73.97643 40.75467) Diversified Financials 350100 627,600,000,000 1,792,631 New York Voya Financial
65 10022 41 -74 34,340 POINT (-73.96787 40.75856) Diversified Financials 350100 627,600,000,000 1,792,631 New York Jefferies Financial
66 85034 33 -112 4,825 POINT (-112.01989 33.43465) Wholesalers: Electronics and Office Equipment 88900 158,200,000,000 1,779,528 Arizona Avnet
67 92612 34 -118 33,706 POINT (-117.82457 33.65984) Wholesalers: Electronics and Office Equipment 88900 158,200,000,000 1,779,528 California Ingram Micro
68 94538 38 -122 67,704 POINT (-121.96361 37.50653) Wholesalers: Electronics and Office Equipment 88900 158,200,000,000 1,779,528 California TD Synnex
69 80112 40 -105 36,687 POINT (-104.85854 39.57288) Wholesalers: Electronics and Office Equipment 88900 158,200,000,000 1,779,528 Colorado Arrow Electronics
70 50392 42 -94 15,018 POINT (-93.628 41.5898) Insurance: Life, Health (Stock) 178200 299,200,000,000 1,679,012 Iowa Principal Financial
71 31999 32 -85 3,469 POINT (-84.98772 32.46078) Insurance: Life, Health (Stock) 178200 299,200,000,000 1,679,012 Georgia Aflac
72 32246 30 -82 60,443 POINT (-81.51782 30.29422) Insurance: Life, Health (Stock) 178200 299,200,000,000 1,679,012 Florida GuideWell Mutual
73 07102 41 -74 12,954 POINT (-74.17343 40.73576) Insurance: Life, Health (Stock) 178200 299,200,000,000 1,679,012 New Jersey Prudential Financial
74 10166 41 -74 0 POINT (-73.9769 40.7531) Insurance: Life, Health (Stock) 178200 299,200,000,000 1,679,012 New York MetLife
75 10105 41 -74 0 POINT (-73.978 40.7644) Insurance: Life, Health (Stock) 178200 299,200,000,000 1,679,012 New York Equitable
76 92660 34 -118 34,788 POINT (-117.87504 33.63375) Insurance: Life, Health (Stock) 178200 299,200,000,000 1,679,012 California Pacific Life
77 63017 39 -91 43,074 POINT (-90.53722 38.65143) Insurance: Life, Health (Stock) 178200 299,200,000,000 1,679,012 Missouri Reinsurance of America
78 37402 35 -85 4,203 POINT (-85.31553 35.04672) Insurance: Life, Health (Stock) 178200 299,200,000,000 1,679,012 Tennessee Unum
79 55101 45 -93 7,937 POINT (-93.08739 44.95111) Insurance: Life, Health (Stock) 178200 299,200,000,000 1,679,012 Minnesota Securian Financial
80 19087 40 -75 33,770 POINT (-75.40004 40.06172) Insurance: Life, Health (Stock) 178200 299,200,000,000 1,679,012 Pennsylvania Lincoln National
In [132]:
musmaxeffin10 = gdfstsusmaxeffin10.explore(column='Efficiency', name='The Most Efficient Industry in US visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactusmaxeffin10.explore(m=musmaxeffin10, column='Efficiency', name='The Most Efficient Industry in US visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(musmaxeffin10)
musmaxeffin10
Out[132]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [133]:
# The Biggest Revenue City in US (other viewpoint)
dfusmaxrevct = df.groupby(['State','City'], as_index=False).sum('Revenue (rounded)').sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
dfusmaxrevct10 = dfusmaxrevct.head(10)
dfusmaxrevct
Out[133]:
State City Employees Revenue (rounded)
0 New York New York 2028200 1,820,500,000,000
1 Texas Houston 557600 906,500,000,000
2 Washington Seattle 2101600 744,900,000,000
3 Arkansas Bentonville 2100000 681,000,000,000
4 Georgia Atlanta 1233700 489,700,000,000
5 Texas Irving 287000 462,000,000,000
6 Nebraska Omaha 463100 427,000,000,000
7 Minnesota Eden Prairie 413800 418,000,000,000
8 California Cupertino 164000 391,000,000,000
9 Texas Spring 121900 379,700,000,000
10 Rhode Island Woonsocket 259500 372,800,000,000
11 Illinois Chicago 724600 368,100,000,000
12 Texas Dallas 590100 366,500,000,000
13 California Mountain View 207500 366,300,000,000
14 North Carolina Charlotte 422700 331,300,000,000
15 California San Francisco 492000 296,000,000,000
16 Pennsylvania Conshohocken 44000 294,000,000,000
17 Ohio Cincinnati 593500 276,100,000,000
18 California Santa Clara 250200 255,600,000,000
19 Washington Issaquah 333000 254,500,000,000
20 Connecticut Bloomfield 72400 247,100,000,000
21 Washington Redmond 228000 245,100,000,000
22 Indiana Indianapolis 172700 238,900,000,000
23 Ohio Dublin 48400 226,800,000,000
24 Michigan Detroit 182200 216,300,000,000
25 Minnesota Minneapolis 573300 211,400,000,000
26 Missouri St. Louis 160700 207,500,000,000
27 Virginia McLean 275900 197,900,000,000
28 District of Columbia Washington 93200 185,200,000,000
29 Michigan Dearborn 171000 185,000,000,000
30 Texas San Antonio 47900 172,600,000,000
31 California Menlo Park 74100 164,500,000,000
32 Illinois Deerfield 290500 162,800,000,000
33 Virginia Arlington 367100 159,500,000,000
34 California San Jose 248200 153,000,000,000
35 Texas Austin 284700 150,700,000,000
36 Pennsylvania Philadelphia 448700 141,100,000,000
37 Ohio Findlay 18300 140,400,000,000
38 Kentucky Louisville 134400 136,600,000,000
39 Connecticut Stamford 225500 132,500,000,000
40 Virginia Richmond 99300 127,000,000,000
41 Tennessee Memphis 559900 124,800,000,000
42 Illinois Bloomington 67400 123,000,000,000
43 New York Purchase 354300 120,100,000,000
44 Pennsylvania Pittsburgh 209800 119,200,000,000
45 Massachusetts Boston 115500 106,400,000,000
46 California Palo Alto 95000 106,000,000,000
47 Idaho Boise 244600 104,300,000,000
48 Wisconsin Milwaukee 106900 96,700,000,000
49 Maryland Bethesda 276000 96,100,000,000
50 Texas Round Rock 108000 95,600,000,000
51 California Burbank 205000 91,400,000,000
52 Ohio Columbus 58700 90,300,000,000
53 Virginia Reston 220000 90,300,000,000
54 New Jersey New Brunswick 138100 88,800,000,000
55 Florida Miami 25300 85,200,000,000
56 North Carolina Mooresville 215500 83,700,000,000
57 New Jersey Newark 50900 80,700,000,000
58 Ohio Cleveland 188400 79,300,000,000
59 Ohio Mayfield Village 66300 75,400,000,000
60 California Fremont 43200 73,400,000,000
61 Arizona Phoenix 121000 73,000,000,000
62 Florida Jacksonville 114900 71,700,000,000
63 Tennessee Nashville 271000 70,600,000,000
64 California San Diego 74800 64,600,000,000
65 New Jersey Rahway 74000 64,200,000,000
66 Illinois Northbrook 55200 64,100,000,000
67 New York Armonk 284500 62,800,000,000
68 Florida Lakeland 255000 60,200,000,000
69 Massachusetts Waltham 128800 60,100,000,000
70 Rhode Island Providence 79600 57,100,000,000
71 Massachusetts Framingham 364000 56,400,000,000
72 Illinois North Chicago 55000 56,300,000,000
73 Massachusetts Springfield 21900 55,000,000,000
74 Texas Fort Worth 133300 54,200,000,000
75 New Jersey Parsippany 38200 54,200,000,000
76 Arkansas Springdale 138000 53,300,000,000
77 Illinois Moline 55500 51,700,000,000
78 Oregon Beaverton 79400 51,400,000,000
79 Colorado Denver 123800 51,200,000,000
80 California Oakland 39800 48,500,000,000
81 Minnesota St. Paul 115100 48,500,000,000
82 New Jersey Princeton 34100 48,300,000,000
83 California Irvine 26100 48,000,000,000
84 Massachusetts Cambridge 84400 44,600,000,000
85 Washington Bellevue 49000 44,300,000,000
86 Florida St. Petersburg 157000 43,800,000,000
87 Michigan Midland 36000 43,000,000,000
88 Connecticut Greenwich 179600 42,800,000,000
89 Illinois Abbott Park 114000 42,000,000,000
90 Minnesota Richfield 85000 41,500,000,000
91 Virginia Newport News 79000 41,100,000,000
92 Virginia Falls Church 97000 41,000,000,000
93 California Long Beach 18000 40,600,000,000
94 Tennessee Goodlettsville 194200 40,600,000,000
95 Minnesota Inver Grove Heights 10700 39,300,000,000
96 California Los Gatos 14000 39,000,000,000
97 Ohio Evendale 53000 38,700,000,000
98 Connecticut Norwalk 64600 38,300,000,000
99 Illinois Rosemont 30000 37,900,000,000
100 Massachusetts Marlborough 86000 37,200,000,000
101 Texas Arlington 14800 36,800,000,000
102 Oregon Medford 30200 36,600,000,000
103 Indiana Columbus 69600 34,100,000,000
104 California Thousand Oaks 28000 33,400,000,000
105 Oklahoma Tulsa 11000 32,200,000,000
106 Ohio Akron 80300 31,900,000,000
107 Virginia Chesapeake 139600 30,800,000,000
108 California Beverly Hills 34200 30,700,000,000
109 Michigan Bloomfield Hills 28900 30,500,000,000
110 Georgia Duluth 39000 28,900,000,000
111 California Foster City 17600 28,800,000,000
112 Nevada Las Vegas 109100 28,500,000,000
113 Colorado Centennial 21500 27,900,000,000
114 Tennessee Brentwood 41000 27,400,000,000
115 Virginia Glen Allen 45200 27,300,000,000
116 California Newport Beach 134800 27,100,000,000
117 Florida Fort Lauderdale 25100 26,800,000,000
118 Connecticut Hartford 19100 26,500,000,000
119 Texas Westlake 32100 26,000,000,000
120 North Carolina Raleigh 65300 25,900,000,000
121 Colorado Englewood 32700 25,800,000,000
122 Illinois Lake Forest 40400 25,600,000,000
123 Florida Coral Gables 82700 24,900,000,000
124 Florida Juno Beach 16800 24,800,000,000
125 Florida Palm Beach Gardens 48000 24,800,000,000
126 Michigan Auburn Hills 100600 24,500,000,000
127 Illinois Riverwoods 21000 23,600,000,000
128 Maryland Baltimore 14200 23,600,000,000
129 Michigan Southfield 173700 23,300,000,000
130 Florida Tampa 36800 22,900,000,000
131 Michigan Portage 53000 22,600,000,000
132 Missouri Chesterfield 4100 22,100,000,000
133 Arizona Scottsdale 19000 22,000,000,000
134 Ohio Maumee 41900 21,600,000,000
135 Florida Melbourne 47000 21,300,000,000
136 Wisconsin Madison 11100 21,300,000,000
137 California Dublin 107000 21,100,000,000
138 Illinois Vernon Hills 15100 21,000,000,000
139 Pennsylvania Allentown 29100 20,600,000,000
140 New Jersey Franklin Lakes 74000 20,200,000,000
141 New Jersey Teaneck 336800 19,700,000,000
142 New Jersey Roseland 64000 19,200,000,000
143 Ohio Toledo 25700 19,000,000,000
144 Georgia Columbus 12700 18,900,000,000
145 Pennsylvania Radnor 9800 18,400,000,000
146 New York Long Island City 30700 18,300,000,000
147 Arkansas El Dorado 11600 17,900,000,000
148 California Rosemead 14000 17,600,000,000
149 Indiana Fort Wayne 13000 17,500,000,000
150 Alabama Birmingham 31600 16,800,000,000
151 Missouri Springfield 85600 16,700,000,000
152 Michigan Benton Harbor 44000 16,600,000,000
153 Arizona Chandler 36600 16,300,000,000
154 California Redwood City 27300 16,300,000,000
155 Missouri Des Peres 55000 16,300,000,000
156 Minnesota Arden Hills 9000 16,200,000,000
157 Wisconsin Menomonee Falls 60000 16,200,000,000
158 Iowa Des Moines 19700 16,100,000,000
159 Oklahoma Oklahoma City 2300 15,900,000,000
160 Illinois Glenview 44000 15,900,000,000
161 Pennsylvania King of Prussia 87500 15,800,000,000
162 Michigan Lansing 7300 15,800,000,000
163 New Jersey Summit 22000 15,500,000,000
164 California Woodland Hills 9900 15,500,000,000
165 North Carolina Durham 88000 15,400,000,000
166 Massachusetts Burlington 29400 15,400,000,000
167 Connecticut New Britain 48500 15,400,000,000
168 Connecticut Wallingford 125000 15,200,000,000
169 Iowa Ankeny 33100 14,900,000,000
170 Pennsylvania Canonsburg 32000 14,700,000,000
171 Tennessee Antioch 47000 14,400,000,000
172 Connecticut Farmington 72000 14,300,000,000
173 New York Tarrytown 15100 14,200,000,000
174 Virginia Ashburn 130000 13,700,000,000
175 Arizona Tempe 17400 13,700,000,000
176 New York Buffalo 22100 13,500,000,000
177 Pennsylvania Coraopolis 37400 13,400,000,000
178 Pennsylvania Erie 6700 13,200,000,000
179 New York Corning 56300 13,100,000,000
180 Louisiana Monroe 25000 13,100,000,000
181 North Carolina Burlington 65400 13,000,000,000
182 Tennessee Chattanooga 10900 12,900,000,000
183 New York Melville 25000 12,700,000,000
184 Tennessee Franklin 52500 12,600,000,000
185 Delaware Wilmington 24000 12,400,000,000
186 Indiana Evansville 42000 12,300,000,000
187 Colorado Westminster 16000 12,100,000,000
188 Arkansas Lowell 33600 12,100,000,000
189 Minnesota Austin 20000 11,900,000,000
190 Louisiana New Orleans 12300 11,900,000,000
191 Florida Plantation 18000 11,900,000,000
192 Illinois Rolling Meadows 56000 11,600,000,000
193 Florida Orlando 191100 11,400,000,000
194 Ohio Fairfield 5600 11,300,000,000
195 Texas Plano 245500 11,300,000,000
196 Nevada Reno 50000 11,300,000,000
197 Illinois Bolingbrook 39000 11,300,000,000
198 Pennsylvania Hershey 19300 11,200,000,000
199 Texas Midland 2000 11,100,000,000
200 Pennsylvania Fort Washington 4900 10,800,000,000
201 Georgia Calhoun 41900 10,800,000,000
202 Wisconsin Oshkosh 18500 10,700,000,000
203 Washington Sumner 39000 10,600,000,000
204 New Jersey Burlington 47300 10,600,000,000
205 Rhode Island Johnston 5800 10,400,000,000
206 Indiana Elkhart 22300 10,000,000,000
207 New York Victor 9300 10,000,000,000
208 Florida Sunny Isles Beach 15000 10,000,000,000
209 New Jersey Secaucus 50500 9,900,000,000
210 California Milpitas 15100 9,800,000,000
211 Virginia Herndon 8100 9,800,000,000
212 California El Segundo 500 9,700,000,000
213 California Newark 450000 9,600,000,000
214 New Jersey Camden 14400 9,600,000,000
215 Michigan Byron Center 15000 9,500,000,000
216 Illinois Oak Brook 12500 9,500,000,000
217 Massachusetts Wilmington 24000 9,400,000,000
218 Tennessee Kingsport 14000 9,400,000,000
219 Kansas Merriam 14000 9,100,000,000
220 Florida Estero 26000 9,000,000,000
221 California Manhattan Beach 15100 9,000,000,000
222 Ohio Mentor 35000 8,800,000,000
223 California San Mateo 10200 8,500,000,000
224 California Sunnyvale 15600 8,400,000,000
225 California Pleasanton 20500 8,400,000,000
226 Illinois Downers Grove 24000 8,400,000,000
227 Minnesota Maplewood 22000 8,300,000,000
228 Ohio Orrville 9000 8,200,000,000
229 Ohio Westerville 31000 8,000,000,000
230 Michigan Livonia 18000 7,800,000,000
231 Texas New Braunfels 7900 7,800,000,000
232 Indiana Warsaw 17000 7,700,000,000
233 California Corona 6000 7,500,000,000
234 Michigan Jackson 8300 7,500,000,000
235 Minnesota Winona 21000 7,500,000,000
236 Illinois Westchester 11200 7,400,000,000
In [135]:
dfusmaxrevct10 = dfusmaxrevct10.merge(df[['State','City','Company','Zip Code']], how = 'inner', on = ['State','City'])

gdfstsusmaxrevct10 = gdfsts.merge(dfusmaxrevct10, how = 'inner', on = ['State'])
gdfusactusmaxrevct10 = gdfusact.merge(dfusmaxrevct10, how = 'inner', on = ['Zip Code']).sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
gdfusactusmaxrevct10
Out[135]:
Zip Code Latitude Longitude Population geometry State City Employees Revenue (rounded) Company
0 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York New York 2028200 1,820,500,000,000 Pfizer
1 10020 41 -74 0 POINT (-73.98071 40.75917) New York New York 2028200 1,820,500,000,000 Sirius XM
2 10022 41 -74 34,340 POINT (-73.96787 40.75856) New York New York 2028200 1,820,500,000,000 Interpublic
3 10022 41 -74 34,340 POINT (-73.96787 40.75856) New York New York 2028200 1,820,500,000,000 Jefferies Financial
4 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York New York 2028200 1,820,500,000,000 Verizon
5 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York New York 2028200 1,820,500,000,000 Morgan Stanley
6 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York New York 2028200 1,820,500,000,000 Paramount Global
7 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York New York 2028200 1,820,500,000,000 Marsh & McLennan
8 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York New York 2028200 1,820,500,000,000 Fox
9 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York New York 2028200 1,820,500,000,000 Hess
10 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York New York 2028200 1,820,500,000,000 News Corp.
11 10153 41 -74 0 POINT (-73.97244 40.76362) New York New York 2028200 1,820,500,000,000 Estée Lauder
12 10154 41 -74 0 POINT (-73.97249 40.75778) New York New York 2028200 1,820,500,000,000 Blackstone
13 10169 41 -74 0 POINT (-73.97643 40.75467) New York New York 2028200 1,820,500,000,000 Voya Financial
14 10282 41 -74 5,960 POINT (-74.01495 40.71655) New York New York 2028200 1,820,500,000,000 Goldman Sachs
15 10041 41 -74 6,217 POINT (-74.01 40.7031) New York New York 2028200 1,820,500,000,000 S&P Global
16 10105 41 -74 0 POINT (-73.978 40.7644) New York New York 2028200 1,820,500,000,000 Equitable
17 10166 41 -74 0 POINT (-73.9769 40.7531) New York New York 2028200 1,820,500,000,000 MetLife
18 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York New York 2028200 1,820,500,000,000 KKR
19 10286 41 -74 5,269 POINT (-74.01182 40.7052) New York New York 2028200 1,820,500,000,000 Bank of New York
20 10285 41 -74 0 POINT (-74.01492 40.71201) New York New York 2028200 1,820,500,000,000 American Express
21 10022 41 -74 34,340 POINT (-73.96787 40.75856) New York New York 2028200 1,820,500,000,000 Colgate-Palmolive
22 10169 41 -74 0 POINT (-73.97643 40.75467) New York New York 2028200 1,820,500,000,000 StoneX
23 10020 41 -74 0 POINT (-73.98071 40.75917) New York New York 2028200 1,820,500,000,000 American International
24 10013 41 -74 28,215 POINT (-74.00472 40.72001) New York New York 2028200 1,820,500,000,000 Citi
25 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York New York 2028200 1,820,500,000,000 Foot Locker
26 10003 41 -74 53,825 POINT (-73.98915 40.73184) New York New York 2028200 1,820,500,000,000 Warner Bros. Discovery
27 10003 41 -74 53,825 POINT (-73.98915 40.73184) New York New York 2028200 1,820,500,000,000 Consolidated Edison
28 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York New York 2028200 1,820,500,000,000 Guardian Life
29 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York New York 2028200 1,820,500,000,000 BlackRock
30 10006 41 -74 4,475 POINT (-74.01306 40.70949) New York New York 2028200 1,820,500,000,000 ABM Industries
31 10010 41 -74 31,905 POINT (-73.98243 40.73899) New York New York 2028200 1,820,500,000,000 New York Life Insurance
32 10019 41 -74 44,276 POINT (-73.9853 40.76586) New York New York 2028200 1,820,500,000,000 International Flavors & Fragrances
33 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York New York 2028200 1,820,500,000,000 Macy's
34 10013 41 -74 28,215 POINT (-74.00472 40.72001) New York New York 2028200 1,820,500,000,000 Oscar Health
35 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York New York 2028200 1,820,500,000,000 JPMorgan Chase
36 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York New York 2028200 1,820,500,000,000 TIAA
37 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York New York 2028200 1,820,500,000,000 Travelers
38 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York New York 2028200 1,820,500,000,000 Kyndryl s
39 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York New York 2028200 1,820,500,000,000 Omnicom
40 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York New York 2028200 1,820,500,000,000 PVH
41 10019 41 -74 44,276 POINT (-73.9853 40.76586) New York New York 2028200 1,820,500,000,000 Apollo Global Management
42 10019 41 -74 44,276 POINT (-73.9853 40.76586) New York New York 2028200 1,820,500,000,000 Loews
43 77019 30 -95 23,662 POINT (-95.41212 29.75318) Texas Houston 557600 906,500,000,000 Corebridge Financial
44 77008 30 -95 40,155 POINT (-95.41766 29.79856) Texas Houston 557600 906,500,000,000 Quanta Services
45 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas Houston 557600 906,500,000,000 KBR
46 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas Houston 557600 906,500,000,000 CenterPoint Energy
47 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas Houston 557600 906,500,000,000 NRG Energy
48 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas Houston 557600 906,500,000,000 Kinder Morgan
49 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas Houston 557600 906,500,000,000 Chevron
50 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas Houston 557600 906,500,000,000 Enterprise Products Partners
51 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas Houston 557600 906,500,000,000 Plains GP
52 77024 30 -96 37,647 POINT (-95.50869 29.77073) Texas Houston 557600 906,500,000,000 Par Pacific
53 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas Houston 557600 906,500,000,000 EOG Resources
54 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas Houston 557600 906,500,000,000 Waste Management
55 77024 30 -96 37,647 POINT (-95.50869 29.77073) Texas Houston 557600 906,500,000,000 1 Automotive
56 77077 30 -96 63,421 POINT (-95.64189 29.75375) Texas Houston 557600 906,500,000,000 Sysco
57 77032 30 -95 13,536 POINT (-95.34004 29.96523) Texas Houston 557600 906,500,000,000 Halliburton
58 77042 30 -96 40,725 POINT (-95.56015 29.74125) Texas Houston 557600 906,500,000,000 Phillips 66
59 77042 30 -96 40,725 POINT (-95.56015 29.74125) Texas Houston 557600 906,500,000,000 APA
60 77042 30 -96 40,725 POINT (-95.56015 29.74125) Texas Houston 557600 906,500,000,000 NOV
61 77046 30 -95 1,873 POINT (-95.43301 29.73438) Texas Houston 557600 906,500,000,000 Occidental Petroleum
62 77056 30 -95 23,314 POINT (-95.46806 29.74849) Texas Houston 557600 906,500,000,000 Westlake
63 77079 30 -96 35,540 POINT (-95.6037 29.77632) Texas Houston 557600 906,500,000,000 ConocoPhillips
64 77079 30 -96 35,540 POINT (-95.6037 29.77632) Texas Houston 557600 906,500,000,000 Baker Hughes
65 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas Houston 557600 906,500,000,000 Cheniere Energy
66 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas Houston 557600 906,500,000,000 Targa Resources
67 98101 48 -122 16,396 POINT (-122.33454 47.61119) Washington Seattle 2101600 744,900,000,000 Coupang
68 98101 48 -122 16,396 POINT (-122.33454 47.61119) Washington Seattle 2101600 744,900,000,000 Nordstrom
69 98109 48 -122 32,552 POINT (-122.34486 47.63128) Washington Seattle 2101600 744,900,000,000 Amazon
70 98119 48 -122 26,390 POINT (-122.36932 47.63943) Washington Seattle 2101600 744,900,000,000 Expedia
71 98134 48 -122 779 POINT (-122.33686 47.57691) Washington Seattle 2101600 744,900,000,000 Starbucks
72 98188 47 -122 26,769 POINT (-122.27398 47.44754) Washington Seattle 2101600 744,900,000,000 Alaska Air
73 72712 36 -94 38,072 POINT (-94.22196 36.39837) Arkansas Bentonville 2100000 681,000,000,000 Walmart
74 30339 34 -84 34,872 POINT (-84.46483 33.86786) Georgia Atlanta 1233700 489,700,000,000 Home Depot
75 30308 34 -84 23,329 POINT (-84.37773 33.77094) Georgia Atlanta 1233700 489,700,000,000 Southern
76 30308 34 -84 23,329 POINT (-84.37773 33.77094) Georgia Atlanta 1233700 489,700,000,000 Norfolk Southern
77 30313 34 -84 10,845 POINT (-84.39761 33.76369) Georgia Atlanta 1233700 489,700,000,000 Coca-Cola
78 30326 34 -84 8,497 POINT (-84.36342 33.84957) Georgia Atlanta 1233700 489,700,000,000 Pulte
79 30326 34 -84 8,497 POINT (-84.36342 33.84957) Georgia Atlanta 1233700 489,700,000,000 Global Payments
80 30328 34 -84 38,821 POINT (-84.38617 33.93194) Georgia Atlanta 1233700 489,700,000,000 UPS
81 30328 34 -84 38,821 POINT (-84.38617 33.93194) Georgia Atlanta 1233700 489,700,000,000 Intercontinental Exchange
82 30328 34 -84 38,821 POINT (-84.38617 33.93194) Georgia Atlanta 1233700 489,700,000,000 Graphic Packaging
83 30328 34 -84 38,821 POINT (-84.38617 33.93194) Georgia Atlanta 1233700 489,700,000,000 Newell Brands
84 30339 34 -84 34,872 POINT (-84.46483 33.86786) Georgia Atlanta 1233700 489,700,000,000 Genuine Parts
85 30339 34 -84 34,872 POINT (-84.46483 33.86786) Georgia Atlanta 1233700 489,700,000,000 Assurant
86 30354 34 -84 15,487 POINT (-84.38609 33.66058) Georgia Atlanta 1233700 489,700,000,000 Delta Airlines
87 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas Irving 287000 462,000,000,000 Celanese
88 75038 33 -97 33,097 POINT (-96.97946 32.87231) Texas Irving 287000 462,000,000,000 Kimberly-Clark
89 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas Irving 287000 462,000,000,000 McKesson
90 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas Irving 287000 462,000,000,000 Caterpillar
91 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas Irving 287000 462,000,000,000 Vistra
92 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas Irving 287000 462,000,000,000 Builders FirstSource
93 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas Irving 287000 462,000,000,000 Fluor
94 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas Irving 287000 462,000,000,000 Commercial Metals
95 68175 41 -96 0 POINT (-95.96584 41.26502) Nebraska Omaha 463100 427,000,000,000 Mutual of Omaha Insurance
96 68179 41 -96 0 POINT (-95.9352 41.2597) Nebraska Omaha 463100 427,000,000,000 Union Pacific
97 68131 41 -96 13,928 POINT (-95.96479 41.26435) Nebraska Omaha 463100 427,000,000,000 Berkshire Hathaway
98 68102 41 -96 9,311 POINT (-95.93224 41.26231) Nebraska Omaha 463100 427,000,000,000 Peter Kiewit Sons'
99 55344 45 -93 14,180 POINT (-93.43037 44.86452) Minnesota Eden Prairie 413800 418,000,000,000 UnitedHealth
100 55347 45 -93 30,467 POINT (-93.46638 44.82931) Minnesota Eden Prairie 413800 418,000,000,000 C.H. Robinson Worldwide
101 95014 37 -122 61,109 POINT (-122.07981 37.30827) California Cupertino 164000 391,000,000,000 Apple
102 77389 30 -96 44,545 POINT (-95.50752 30.11509) Texas Spring 121900 379,700,000,000 Hewlett Packard
103 77389 30 -96 44,545 POINT (-95.50752 30.11509) Texas Spring 121900 379,700,000,000 Exxon Mobil
In [136]:
musmaxrevct10 = gdfstsusmaxrevct10.explore(column='Revenue (rounded)', name='The Biggest Revenue City in US visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactusmaxrevct10.explore(m=musmaxrevct10, column='Revenue (rounded)', name='The Biggest Revenue City in US visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(musmaxrevct10)
musmaxrevct10
Out[136]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [137]:
# The Biggest Revenue State in US (other viewpoint)
dfusmaxrevst = df.groupby(['State'], as_index=False).sum('Revenue (rounded)').sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
dfusmaxrevst10 = dfusmaxrevst.head(10)
dfusmaxrevst
Out[137]:
State Employees Revenue (rounded)
0 Texas 2432800 2,680,800,000,000
1 California 2857700 2,399,300,000,000
2 New York 2825500 2,085,200,000,000
3 Washington 2750600 1,299,400,000,000
4 Illinois 1655400 1,040,200,000,000
5 Ohio 1255100 1,035,800,000,000
6 Minnesota 1269900 802,600,000,000
7 Arkansas 2283200 764,300,000,000
8 Virginia 1461200 738,400,000,000
9 Pennsylvania 929200 672,400,000,000
10 Michigan 838000 602,400,000,000
11 Georgia 1327300 548,300,000,000
12 Connecticut 806700 532,100,000,000
13 North Carolina 856900 469,300,000,000
14 Florida 1058700 448,700,000,000
15 New Jersey 944300 440,900,000,000
16 Rhode Island 344900 440,300,000,000
17 Nebraska 463100 427,000,000,000
18 Massachusetts 854000 384,500,000,000
19 Indiana 336600 320,500,000,000
20 Tennessee 1190500 312,700,000,000
21 Missouri 305400 262,600,000,000
22 District of Columbia 93200 185,200,000,000
23 Wisconsin 196500 144,900,000,000
24 Kentucky 134400 136,600,000,000
25 Arizona 194000 125,000,000,000
26 Maryland 290200 119,700,000,000
27 Colorado 194000 117,000,000,000
28 Idaho 244600 104,300,000,000
29 Oregon 109600 88,000,000,000
30 Oklahoma 13300 48,100,000,000
31 Nevada 159100 39,800,000,000
32 Iowa 52800 31,000,000,000
33 Louisiana 37300 25,000,000,000
34 Alabama 31600 16,800,000,000
35 Delaware 24000 12,400,000,000
36 Kansas 14000 9,100,000,000
In [138]:
dfusmaxrevst10 = dfusmaxrevst10.merge(df[['State','City','Company','Zip Code']], how = 'inner', on = ['State'])

gdfstsusmaxrevst10 = gdfsts.merge(dfusmaxrevst10, how = 'inner', on = ['State'])
gdfusactusmaxrevst10 = gdfusact.merge(dfusmaxrevst10, how = 'inner', on = ['Zip Code']).sort_values('Revenue (rounded)', ascending=False).reset_index(drop=True)
gdfusactusmaxrevst10
Out[138]:
Zip Code Latitude Longitude Population geometry State Employees Revenue (rounded) City Company
0 75038 33 -97 33,097 POINT (-96.97946 32.87231) Texas 2432800 2,680,800,000,000 Irving Kimberly-Clark
1 77042 30 -96 40,725 POINT (-95.56015 29.74125) Texas 2432800 2,680,800,000,000 Houston NOV
2 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston Cheniere Energy
3 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston Kinder Morgan
4 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston CenterPoint Energy
5 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston KBR
6 77008 30 -95 40,155 POINT (-95.41766 29.79856) Texas 2432800 2,680,800,000,000 Houston Quanta Services
7 77019 30 -95 23,662 POINT (-95.41212 29.75318) Texas 2432800 2,680,800,000,000 Houston Corebridge Financial
8 77024 30 -96 37,647 POINT (-95.50869 29.77073) Texas 2432800 2,680,800,000,000 Houston 1 Automotive
9 77024 30 -96 37,647 POINT (-95.50869 29.77073) Texas 2432800 2,680,800,000,000 Houston Par Pacific
10 77032 30 -95 13,536 POINT (-95.34004 29.96523) Texas 2432800 2,680,800,000,000 Houston Halliburton
11 77042 30 -96 40,725 POINT (-95.56015 29.74125) Texas 2432800 2,680,800,000,000 Houston Phillips 66
12 77042 30 -96 40,725 POINT (-95.56015 29.74125) Texas 2432800 2,680,800,000,000 Houston APA
13 77046 30 -95 1,873 POINT (-95.43301 29.73438) Texas 2432800 2,680,800,000,000 Houston Occidental Petroleum
14 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston EOG Resources
15 77056 30 -95 23,314 POINT (-95.46806 29.74849) Texas 2432800 2,680,800,000,000 Houston Westlake
16 77077 30 -96 63,421 POINT (-95.64189 29.75375) Texas 2432800 2,680,800,000,000 Houston Sysco
17 77079 30 -96 35,540 POINT (-95.6037 29.77632) Texas 2432800 2,680,800,000,000 Houston ConocoPhillips
18 77079 30 -96 35,540 POINT (-95.6037 29.77632) Texas 2432800 2,680,800,000,000 Houston Baker Hughes
19 77389 30 -96 44,545 POINT (-95.50752 30.11509) Texas 2432800 2,680,800,000,000 Spring Exxon Mobil
20 77389 30 -96 44,545 POINT (-95.50752 30.11509) Texas 2432800 2,680,800,000,000 Spring Hewlett Packard
21 78130 30 -98 95,787 POINT (-98.06877 29.69224) Texas 2432800 2,680,800,000,000 New Braunfels Rush Enterprises
22 78249 30 -99 61,772 POINT (-98.614 29.56752) Texas 2432800 2,680,800,000,000 San Antonio Valero Energy
23 78725 30 -98 10,810 POINT (-97.60859 30.23554) Texas 2432800 2,680,800,000,000 Austin Tesla
24 78741 30 -98 45,274 POINT (-97.71389 30.23007) Texas 2432800 2,680,800,000,000 Austin Oracle
25 79701 32 -102 27,678 POINT (-102.08105 31.99239) Texas 2432800 2,680,800,000,000 Midland Diamondback Energy
26 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston Waste Management
27 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston Targa Resources
28 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston NRG Energy
29 75202 33 -97 2,744 POINT (-96.8037 32.77843) Texas 2432800 2,680,800,000,000 Dallas AT&T
30 78682 30 -98 0 POINT (-97.7273 30.4076) Texas 2432800 2,680,800,000,000 Round Rock Dell Technologies
31 78288 29 -98 0 POINT (-98.4935 29.4239) Texas 2432800 2,680,800,000,000 San Antonio USAA
32 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 Irving McKesson
33 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 Irving Caterpillar
34 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 Irving Vistra
35 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 Irving Builders FirstSource
36 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 Irving Fluor
37 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 Irving Celanese
38 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 Irving Commercial Metals
39 75074 33 -97 53,146 POINT (-96.67304 33.03298) Texas 2432800 2,680,800,000,000 Plano Yum China s
40 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston Plains GP
41 75201 33 -97 18,078 POINT (-96.79953 32.78826) Texas 2432800 2,680,800,000,000 Dallas Jacobs Solutions
42 75201 33 -97 18,078 POINT (-96.79953 32.78826) Texas 2432800 2,680,800,000,000 Dallas CBRE
43 75219 33 -97 25,001 POINT (-96.81315 32.81087) Texas 2432800 2,680,800,000,000 Dallas HF Sinclair
44 76011 33 -97 22,297 POINT (-97.08223 32.7543) Texas 2432800 2,680,800,000,000 Arlington D.R. Horton
45 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston Enterprise Products Partners
46 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston Chevron
47 75225 33 -97 22,383 POINT (-96.79109 32.86511) Texas 2432800 2,680,800,000,000 Dallas Energy Transfer
48 76155 33 -97 6,301 POINT (-97.04911 32.82404) Texas 2432800 2,680,800,000,000 Fort Worth American Airlines
49 76262 33 -97 43,589 POINT (-97.22101 33.01137) Texas 2432800 2,680,800,000,000 Westlake Charles Schwab
50 75254 33 -97 24,737 POINT (-96.80127 32.94571) Texas 2432800 2,680,800,000,000 Dallas Tenet Healthcare
51 75243 33 -97 63,907 POINT (-96.73633 32.91232) Texas 2432800 2,680,800,000,000 Dallas Texas Instruments
52 75240 33 -97 24,718 POINT (-96.78924 32.93194) Texas 2432800 2,680,800,000,000 Dallas AECOM
53 75235 33 -97 19,067 POINT (-96.84798 32.83219) Texas 2432800 2,680,800,000,000 Dallas Southwest Airlines
54 91320 34 -119 43,628 POINT (-118.94795 34.17339) California 2857700 2,399,300,000,000 Thousand Oaks Amgen
55 90210 34 -118 19,652 POINT (-118.41505 34.10251) California 2857700 2,399,300,000,000 Beverly Hills Live Nation Entertainment
56 90210 34 -118 19,652 POINT (-118.41505 34.10251) California 2857700 2,399,300,000,000 Beverly Hills Endeavor
57 90245 34 -118 16,863 POINT (-118.40161 33.91709) California 2857700 2,399,300,000,000 El Segundo A-Mark Precious Metals
58 90266 34 -118 34,584 POINT (-118.39705 33.88968) California 2857700 2,399,300,000,000 Manhattan Beach Skechers U.S.A.
59 90802 34 -118 39,859 POINT (-118.21143 33.75035) California 2857700 2,399,300,000,000 Long Beach Molina Healthcare
60 91521 34 -118 11,049 POINT (-118.3252 34.1569) California 2857700 2,399,300,000,000 Burbank Walt Disney
61 91367 34 -119 45,427 POINT (-118.61518 34.17708) California 2857700 2,399,300,000,000 Woodland Hills Farmers Insurance Exchange
62 95054 37 -122 25,196 POINT (-121.96483 37.39308) California 2857700 2,399,300,000,000 Santa Clara Intel
63 94538 38 -122 67,704 POINT (-121.96361 37.50653) California 2857700 2,399,300,000,000 Fremont TD Synnex
64 94560 38 -122 47,145 POINT (-122.02523 37.50771) California 2857700 2,399,300,000,000 Newark Concentrix
65 94568 38 -122 70,542 POINT (-121.90113 37.71596) California 2857700 2,399,300,000,000 Dublin Ross Stores
66 94588 38 -122 34,423 POINT (-121.88178 37.73801) California 2857700 2,399,300,000,000 Pleasanton Workday
67 94612 38 -122 17,663 POINT (-122.2662 37.80789) California 2857700 2,399,300,000,000 Oakland PG&E
68 94612 38 -122 17,663 POINT (-122.2662 37.80789) California 2857700 2,399,300,000,000 Oakland Block
69 95014 37 -122 61,109 POINT (-122.07981 37.30827) California 2857700 2,399,300,000,000 Cupertino Apple
70 95032 37 -122 27,682 POINT (-121.92359 37.20859) California 2857700 2,399,300,000,000 Los Gatos Netflix
71 95035 37 -122 78,479 POINT (-121.87632 37.44319) California 2857700 2,399,300,000,000 Milpitas KLA
72 95051 37 -122 61,345 POINT (-121.98444 37.3483) California 2857700 2,399,300,000,000 Santa Clara Nvidia
73 95054 37 -122 25,196 POINT (-121.96483 37.39308) California 2857700 2,399,300,000,000 Santa Clara Applied Materials
74 94403 38 -122 43,459 POINT (-122.30454 37.53844) California 2857700 2,399,300,000,000 San Mateo Franklin Resources
75 95054 37 -122 25,196 POINT (-121.96483 37.39308) California 2857700 2,399,300,000,000 Santa Clara Advanced Micro Devices
76 95054 37 -122 25,196 POINT (-121.96483 37.39308) California 2857700 2,399,300,000,000 Santa Clara ServiceNow
77 95054 37 -122 25,196 POINT (-121.96483 37.39308) California 2857700 2,399,300,000,000 Santa Clara Palo Alto Networks
78 95110 37 -122 19,444 POINT (-121.9097 37.34656) California 2857700 2,399,300,000,000 San Jose Adobe
79 95119 37 -122 10,449 POINT (-121.79077 37.22756) California 2857700 2,399,300,000,000 San Jose Western Digital
80 95125 37 -122 53,934 POINT (-121.89408 37.29554) California 2857700 2,399,300,000,000 San Jose Ebay
81 95131 37 -122 30,745 POINT (-121.89793 37.38729) California 2857700 2,399,300,000,000 San Jose PayPal
82 95131 37 -122 30,745 POINT (-121.89793 37.38729) California 2857700 2,399,300,000,000 San Jose Super Micro Computer
83 95134 37 -122 30,255 POINT (-121.94528 37.43003) California 2857700 2,399,300,000,000 San Jose Cisco Systems
84 95134 37 -122 30,255 POINT (-121.94528 37.43003) California 2857700 2,399,300,000,000 San Jose Sanmina
85 94404 38 -122 35,950 POINT (-122.26905 37.5562) California 2857700 2,399,300,000,000 Foster City Gilead Sciences
86 94538 38 -122 67,704 POINT (-121.96361 37.50653) California 2857700 2,399,300,000,000 Fremont Lam Research
87 94304 37 -122 4,731 POINT (-122.16699 37.39744) California 2857700 2,399,300,000,000 Palo Alto Broadcom
88 94065 38 -122 11,620 POINT (-122.24683 37.53504) California 2857700 2,399,300,000,000 Redwood City Electronic Arts
89 92101 33 -117 48,163 POINT (-117.18589 32.7162) California 2857700 2,399,300,000,000 San Diego Sempra
90 92121 33 -117 4,157 POINT (-117.20231 32.8973) California 2857700 2,399,300,000,000 San Diego Qualcomm
91 92121 33 -117 4,157 POINT (-117.20231 32.8973) California 2857700 2,399,300,000,000 San Diego LPL Financial s
92 92612 34 -118 33,706 POINT (-117.82457 33.65984) California 2857700 2,399,300,000,000 Irvine Ingram Micro
93 92660 34 -118 34,788 POINT (-117.87504 33.63375) California 2857700 2,399,300,000,000 Newport Beach Pacific Life
94 92660 34 -118 34,788 POINT (-117.87504 33.63375) California 2857700 2,399,300,000,000 Newport Beach Chipotle Mexican Grill
95 92879 34 -118 48,756 POINT (-117.5357 33.87979) California 2857700 2,399,300,000,000 Corona Monster Beverage
96 94025 37 -122 40,230 POINT (-122.1829 37.45087) California 2857700 2,399,300,000,000 Menlo Park Meta
97 94304 37 -122 4,731 POINT (-122.16699 37.39744) California 2857700 2,399,300,000,000 Palo Alto HP
98 94043 37 -122 32,042 POINT (-122.06892 37.41188) California 2857700 2,399,300,000,000 Mountain View Intuit
99 94065 38 -122 11,620 POINT (-122.24683 37.53504) California 2857700 2,399,300,000,000 Redwood City Equinix
100 94043 37 -122 32,042 POINT (-122.06892 37.41188) California 2857700 2,399,300,000,000 Mountain View Alphabet
101 94086 37 -122 48,956 POINT (-122.02316 37.37164) California 2857700 2,399,300,000,000 Sunnyvale Intuitive Surgical
102 94107 38 -122 30,190 POINT (-122.39508 37.76473) California 2857700 2,399,300,000,000 San Francisco DoorDash
103 94158 38 -122 11,206 POINT (-122.39153 37.77116) California 2857700 2,399,300,000,000 San Francisco Uber
104 94103 38 -122 33,524 POINT (-122.41136 37.77299) California 2857700 2,399,300,000,000 San Francisco Airbnb
105 94111 38 -122 4,553 POINT (-122.3998 37.79847) California 2857700 2,399,300,000,000 San Francisco Prologis
106 94109 38 -122 54,397 POINT (-122.42138 37.79334) California 2857700 2,399,300,000,000 San Francisco Williams-Sonoma
107 91770 34 -118 58,893 POINT (-118.08361 34.06395) California 2857700 2,399,300,000,000 Rosemead Edison International
108 94105 38 -122 14,890 POINT (-122.39707 37.79239) California 2857700 2,399,300,000,000 San Francisco Gap
109 94105 38 -122 14,890 POINT (-122.39707 37.79239) California 2857700 2,399,300,000,000 San Francisco Visa
110 94105 38 -122 14,890 POINT (-122.39707 37.79239) California 2857700 2,399,300,000,000 San Francisco Salesforce
111 94104 38 -122 478 POINT (-122.40211 37.79144) California 2857700 2,399,300,000,000 San Francisco Wells Fargo
112 10041 41 -74 6,217 POINT (-74.01 40.7031) New York 2825500 2,085,200,000,000 New York S&P Global
113 10105 41 -74 0 POINT (-73.978 40.7644) New York 2825500 2,085,200,000,000 New York Equitable
114 10166 41 -74 0 POINT (-73.9769 40.7531) New York 2825500 2,085,200,000,000 New York MetLife
115 10285 41 -74 0 POINT (-74.01492 40.71201) New York 2825500 2,085,200,000,000 New York American Express
116 10286 41 -74 5,269 POINT (-74.01182 40.7052) New York 2825500 2,085,200,000,000 New York Bank of New York
117 14831 42 -77 5,986 POINT (-77.0553 42.1429) New York 2825500 2,085,200,000,000 Corning Corning
118 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York 2825500 2,085,200,000,000 New York KKR
119 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York 2825500 2,085,200,000,000 New York Pfizer
120 10591 41 -74 23,663 POINT (-73.84653 41.08436) New York 2825500 2,085,200,000,000 Tarrytown Regeneron Pharmaceuticals
121 10022 41 -74 34,340 POINT (-73.96787 40.75856) New York 2825500 2,085,200,000,000 New York Jefferies Financial
122 10022 41 -74 34,340 POINT (-73.96787 40.75856) New York 2825500 2,085,200,000,000 New York Colgate-Palmolive
123 10020 41 -74 0 POINT (-73.98071 40.75917) New York 2825500 2,085,200,000,000 New York Sirius XM
124 10020 41 -74 0 POINT (-73.98071 40.75917) New York 2825500 2,085,200,000,000 New York American International
125 10577 41 -74 5,901 POINT (-73.71349 41.03755) New York 2825500 2,085,200,000,000 Purchase Mastercard
126 10019 41 -74 44,276 POINT (-73.9853 40.76586) New York 2825500 2,085,200,000,000 New York Loews
127 10019 41 -74 44,276 POINT (-73.9853 40.76586) New York 2825500 2,085,200,000,000 New York Apollo Global Management
128 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York 2825500 2,085,200,000,000 New York PVH
129 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York 2825500 2,085,200,000,000 New York Omnicom
130 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York 2825500 2,085,200,000,000 New York Kyndryl s
131 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York 2825500 2,085,200,000,000 New York Travelers
132 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York 2825500 2,085,200,000,000 New York TIAA
133 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York 2825500 2,085,200,000,000 New York JPMorgan Chase
134 10013 41 -74 28,215 POINT (-74.00472 40.72001) New York 2825500 2,085,200,000,000 New York Oscar Health
135 10013 41 -74 28,215 POINT (-74.00472 40.72001) New York 2825500 2,085,200,000,000 New York Citi
136 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York 2825500 2,085,200,000,000 New York Guardian Life
137 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York 2825500 2,085,200,000,000 New York Foot Locker
138 10003 41 -74 53,825 POINT (-73.98915 40.73184) New York 2825500 2,085,200,000,000 New York Warner Bros. Discovery
139 10003 41 -74 53,825 POINT (-73.98915 40.73184) New York 2825500 2,085,200,000,000 New York Consolidated Edison
140 10006 41 -74 4,475 POINT (-74.01306 40.70949) New York 2825500 2,085,200,000,000 New York ABM Industries
141 10022 41 -74 34,340 POINT (-73.96787 40.75856) New York 2825500 2,085,200,000,000 New York Interpublic
142 10019 41 -74 44,276 POINT (-73.9853 40.76586) New York 2825500 2,085,200,000,000 New York International Flavors & Fragrances
143 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York 2825500 2,085,200,000,000 New York Verizon
144 10504 41 -74 7,853 POINT (-73.70629 41.13065) New York 2825500 2,085,200,000,000 Armonk IBM
145 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York 2825500 2,085,200,000,000 New York Macy's
146 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York 2825500 2,085,200,000,000 New York BlackRock
147 11101 41 -74 39,007 POINT (-73.93916 40.74679) New York 2825500 2,085,200,000,000 Long Island City JetBlue Airways
148 11101 41 -74 39,007 POINT (-73.93916 40.74679) New York 2825500 2,085,200,000,000 Long Island City Altice USA
149 11747 41 -73 19,826 POINT (-73.40931 40.78372) New York 2825500 2,085,200,000,000 Melville Henry Schein
150 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York 2825500 2,085,200,000,000 New York Morgan Stanley
151 14203 43 -79 2,526 POINT (-78.86507 42.86244) New York 2825500 2,085,200,000,000 Buffalo M&T Bank
152 14564 43 -77 16,257 POINT (-77.42417 42.98329) New York 2825500 2,085,200,000,000 Victor Constellation Brands
153 10577 41 -74 5,901 POINT (-73.71349 41.03755) New York 2825500 2,085,200,000,000 Purchase PepsiCo
154 10010 41 -74 31,905 POINT (-73.98243 40.73899) New York 2825500 2,085,200,000,000 New York New York Life Insurance
155 10282 41 -74 5,960 POINT (-74.01495 40.71655) New York 2825500 2,085,200,000,000 New York Goldman Sachs
156 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York 2825500 2,085,200,000,000 New York News Corp.
157 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York 2825500 2,085,200,000,000 New York Paramount Global
158 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York 2825500 2,085,200,000,000 New York Marsh & McLennan
159 10169 41 -74 0 POINT (-73.97643 40.75467) New York 2825500 2,085,200,000,000 New York Voya Financial
160 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York 2825500 2,085,200,000,000 New York Hess
161 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York 2825500 2,085,200,000,000 New York Fox
162 10153 41 -74 0 POINT (-73.97244 40.76362) New York 2825500 2,085,200,000,000 New York Estée Lauder
163 10154 41 -74 0 POINT (-73.97249 40.75778) New York 2825500 2,085,200,000,000 New York Blackstone
164 10169 41 -74 0 POINT (-73.97643 40.75467) New York 2825500 2,085,200,000,000 New York StoneX
165 98052 48 -122 79,074 POINT (-122.1203 47.68148) Washington 2750600 1,299,400,000,000 Redmond Microsoft
166 98027 48 -122 28,335 POINT (-122.00176 47.50387) Washington 2750600 1,299,400,000,000 Issaquah Costco
167 98006 48 -122 40,770 POINT (-122.14957 47.55772) Washington 2750600 1,299,400,000,000 Bellevue Expeditors International of Washington
168 98101 48 -122 16,396 POINT (-122.33454 47.61119) Washington 2750600 1,299,400,000,000 Seattle Coupang
169 98101 48 -122 16,396 POINT (-122.33454 47.61119) Washington 2750600 1,299,400,000,000 Seattle Nordstrom
170 98109 48 -122 32,552 POINT (-122.34486 47.63128) Washington 2750600 1,299,400,000,000 Seattle Amazon
171 98119 48 -122 26,390 POINT (-122.36932 47.63943) Washington 2750600 1,299,400,000,000 Seattle Expedia
172 98134 48 -122 779 POINT (-122.33686 47.57691) Washington 2750600 1,299,400,000,000 Seattle Starbucks
173 98188 47 -122 26,769 POINT (-122.27398 47.44754) Washington 2750600 1,299,400,000,000 Seattle Alaska Air
174 98390 47 -122 11,497 POINT (-122.22894 47.21195) Washington 2750600 1,299,400,000,000 Sumner Lululemon athletica
175 98004 48 -122 39,435 POINT (-122.20548 47.61865) Washington 2750600 1,299,400,000,000 Bellevue Paccar
176 60607 42 -88 30,197 POINT (-87.65175 41.87467) Illinois 1655400 1,040,200,000,000 Chicago Mondelez
177 60654 42 -88 24,303 POINT (-87.63673 41.89209) Illinois 1655400 1,040,200,000,000 Chicago Conagra Brands
178 60440 42 -88 52,074 POINT (-88.07572 41.70125) Illinois 1655400 1,040,200,000,000 Bolingbrook Ulta Beauty
179 60661 42 -88 11,516 POINT (-87.64409 41.88291) Illinois 1655400 1,040,200,000,000 Chicago Motorola Solutions
180 61265 41 -90 43,851 POINT (-90.48895 41.48195) Illinois 1655400 1,040,200,000,000 Moline Deere
181 60607 42 -88 30,197 POINT (-87.65175 41.87467) Illinois 1655400 1,040,200,000,000 Chicago McDonald's
182 60606 42 -88 3,527 POINT (-87.63724 41.88178) Illinois 1655400 1,040,200,000,000 Chicago Molson Coors Beverage
183 60606 42 -88 3,527 POINT (-87.63724 41.88178) Illinois 1655400 1,040,200,000,000 Chicago United Airlines
184 60603 42 -88 1,126 POINT (-87.6274 41.88018) Illinois 1655400 1,040,200,000,000 Chicago Northern Trust
185 60603 42 -88 1,126 POINT (-87.6274 41.88018) Illinois 1655400 1,040,200,000,000 Chicago Exelon
186 60601 42 -88 16,292 POINT (-87.62197 41.88527) Illinois 1655400 1,040,200,000,000 Chicago Old Republic International
187 60601 42 -88 16,292 POINT (-87.62197 41.88527) Illinois 1655400 1,040,200,000,000 Chicago Jones Lang LaSalle
188 60601 42 -88 16,292 POINT (-87.62197 41.88527) Illinois 1655400 1,040,200,000,000 Chicago Kraft Heinz
189 60601 42 -88 16,292 POINT (-87.62197 41.88527) Illinois 1655400 1,040,200,000,000 Chicago Archer Daniels Midland
190 60523 42 -88 10,012 POINT (-87.95406 41.83713) Illinois 1655400 1,040,200,000,000 Oak Brook Ace Hardware
191 60515 42 -88 29,045 POINT (-88.0247 41.80991) Illinois 1655400 1,040,200,000,000 Downers Grove Dover
192 60154 42 -88 16,524 POINT (-87.88986 41.84923) Illinois 1655400 1,040,200,000,000 Westchester Ingredion
193 60654 42 -88 24,303 POINT (-87.63673 41.89209) Illinois 1655400 1,040,200,000,000 Chicago Kellanova
194 60064 42 -88 15,047 POINT (-87.86122 42.3237) Illinois 1655400 1,040,200,000,000 Abbott Park Abbott Laboratories
195 60064 42 -88 15,047 POINT (-87.86122 42.3237) Illinois 1655400 1,040,200,000,000 North Chicago AbbVie
196 60062 42 -88 41,667 POINT (-87.84235 42.12663) Illinois 1655400 1,040,200,000,000 Northbrook Allstate
197 60061 42 -88 27,883 POINT (-87.96046 42.2334) Illinois 1655400 1,040,200,000,000 Vernon Hills CDW
198 60045 42 -88 20,957 POINT (-87.87006 42.23807) Illinois 1655400 1,040,200,000,000 Lake Forest Packaging Corp. of America
199 60045 42 -88 20,957 POINT (-87.87006 42.23807) Illinois 1655400 1,040,200,000,000 Lake Forest W.W. Grainger
200 60025 42 -88 40,877 POINT (-87.81204 42.07466) Illinois 1655400 1,040,200,000,000 Glenview Illinois Tool Works
201 60018 42 -88 29,302 POINT (-87.89846 41.99629) Illinois 1655400 1,040,200,000,000 Rosemont US Foods
202 60015 42 -88 27,720 POINT (-87.87486 42.17239) Illinois 1655400 1,040,200,000,000 Deerfield Baxter International
203 60015 42 -88 27,720 POINT (-87.87486 42.17239) Illinois 1655400 1,040,200,000,000 Riverwoods Discover Financial
204 60015 42 -88 27,720 POINT (-87.87486 42.17239) Illinois 1655400 1,040,200,000,000 Deerfield Walgreens
205 60008 42 -88 22,949 POINT (-88.0229 42.0739) Illinois 1655400 1,040,200,000,000 Rolling Meadows Arthur J. Gallagher
206 61710 41 -89 79,633 POINT (-88.9894 40.516) Illinois 1655400 1,040,200,000,000 Bloomington State Farm
207 60661 42 -88 11,516 POINT (-87.64409 41.88291) Illinois 1655400 1,040,200,000,000 Chicago GE HealthCare Technologies
208 44143 42 -81 24,337 POINT (-81.47513 41.55358) Ohio 1255100 1,035,800,000,000 Mayfield Village Progressive
209 44124 41 -81 40,046 POINT (-81.46774 41.49999) Ohio 1255100 1,035,800,000,000 Cleveland Parker-Hannifin
210 45014 39 -85 45,652 POINT (-84.5521 39.32822) Ohio 1255100 1,035,800,000,000 Fairfield Cincinnati Financial
211 44308 41 -82 1,261 POINT (-81.51751 41.0818) Ohio 1255100 1,035,800,000,000 Akron FirstEnergy
212 44115 41 -82 10,389 POINT (-81.66999 41.49211) Ohio 1255100 1,035,800,000,000 Cleveland Sherwin-Williams
213 44114 42 -82 7,472 POINT (-81.67625 41.5137) Ohio 1255100 1,035,800,000,000 Cleveland KeyCorp
214 44114 42 -82 7,472 POINT (-81.67625 41.5137) Ohio 1255100 1,035,800,000,000 Cleveland Cleveland-Cliffs
215 44060 42 -81 60,257 POINT (-81.32806 41.67742) Ohio 1255100 1,035,800,000,000 Mentor Avery Dennison
216 43615 42 -84 40,813 POINT (-83.67255 41.65045) Ohio 1255100 1,035,800,000,000 Toledo Welltower
217 43537 42 -84 29,639 POINT (-83.68542 41.57433) Ohio 1255100 1,035,800,000,000 Maumee Dana
218 43537 42 -84 29,639 POINT (-83.68542 41.57433) Ohio 1255100 1,035,800,000,000 Maumee Andersons
219 43215 40 -83 16,999 POINT (-83.01262 39.96633) Ohio 1255100 1,035,800,000,000 Columbus American Electric Power
220 43215 40 -83 16,999 POINT (-83.01262 39.96633) Ohio 1255100 1,035,800,000,000 Columbus Nationwide
221 43082 40 -83 33,799 POINT (-82.88437 40.15537) Ohio 1255100 1,035,800,000,000 Westerville Vertiv s
222 43017 40 -83 41,422 POINT (-83.13314 40.1189) Ohio 1255100 1,035,800,000,000 Dublin Cardinal Health
223 44667 41 -82 13,688 POINT (-81.76495 40.83386) Ohio 1255100 1,035,800,000,000 Orrville J.M. Smucker
224 45202 39 -85 17,022 POINT (-84.50243 39.10885) Ohio 1255100 1,035,800,000,000 Cincinnati Kroger
225 45202 39 -85 17,022 POINT (-84.50243 39.10885) Ohio 1255100 1,035,800,000,000 Cincinnati Procter & Gamble
226 45202 39 -85 17,022 POINT (-84.50243 39.10885) Ohio 1255100 1,035,800,000,000 Cincinnati Western & Southern Financial
227 45202 39 -85 17,022 POINT (-84.50243 39.10885) Ohio 1255100 1,035,800,000,000 Cincinnati American Financial
228 45215 39 -84 30,806 POINT (-84.46221 39.23536) Ohio 1255100 1,035,800,000,000 Evendale General Electric
229 45840 41 -84 54,342 POINT (-83.64943 41.02626) Ohio 1255100 1,035,800,000,000 Findlay Marathon Petroleum
230 43287 40 -83 905,748 POINT (-83.0011 39.9619) Ohio 1255100 1,035,800,000,000 Columbus Huntington Bancshares
231 43659 42 -84 0 POINT (-83.5554 41.6639) Ohio 1255100 1,035,800,000,000 Toledo Owens Corning
232 44316 41 -81 0 POINT (-81.47083 41.07854) Ohio 1255100 1,035,800,000,000 Akron Goodyear Tire & Rubber
233 45262 39 -84 0 POINT (-84.4569 39.1616) Ohio 1255100 1,035,800,000,000 Cincinnati Cintas
234 45263 39 -84 0 POINT (-84.4569 39.1616) Ohio 1255100 1,035,800,000,000 Cincinnati Fifth Third Bancorp
235 44115 41 -82 10,389 POINT (-81.66999 41.49211) Ohio 1255100 1,035,800,000,000 Cleveland TransDigm
236 55144 45 -93 11,636 POINT (-93.04758 44.92912) Minnesota 1269900 802,600,000,000 St. Paul 3M
237 55474 45 -93 28,071 POINT (-93.27 44.98) Minnesota 1269900 802,600,000,000 Minneapolis Ameriprise Financial
238 55144 45 -93 11,636 POINT (-93.04758 44.92912) Minnesota 1269900 802,600,000,000 Maplewood Solventum
239 55403 45 -93 17,354 POINT (-93.28588 44.97023) Minnesota 1269900 802,600,000,000 Minneapolis Target
240 55126 45 -93 27,484 POINT (-93.13581 45.08614) Minnesota 1269900 802,600,000,000 Arden Hills Land O'Lakes
241 55415 45 -93 6,474 POINT (-93.2578 44.97463) Minnesota 1269900 802,600,000,000 Minneapolis Thrivent Financial for Lutherans
242 55077 45 -93 14,585 POINT (-93.07574 44.81989) Minnesota 1269900 802,600,000,000 Inver Grove Heights CHS
243 55101 45 -93 7,937 POINT (-93.08739 44.95111) Minnesota 1269900 802,600,000,000 St. Paul Securian Financial
244 55102 45 -93 19,565 POINT (-93.12149 44.93216) Minnesota 1269900 802,600,000,000 St. Paul Ecolab
245 55344 45 -93 14,180 POINT (-93.43037 44.86452) Minnesota 1269900 802,600,000,000 Eden Prairie UnitedHealth
246 55347 45 -93 30,467 POINT (-93.46638 44.82931) Minnesota 1269900 802,600,000,000 Eden Prairie C.H. Robinson Worldwide
247 55401 45 -93 11,526 POINT (-93.26984 44.98526) Minnesota 1269900 802,600,000,000 Minneapolis Xcel Energy
248 55402 45 -93 760 POINT (-93.27119 44.97608) Minnesota 1269900 802,600,000,000 Minneapolis U.S. Bancorp
249 55987 44 -92 33,911 POINT (-91.63143 43.98469) Minnesota 1269900 802,600,000,000 Winona Fastenal
250 55912 44 -93 29,438 POINT (-92.99148 43.6827) Minnesota 1269900 802,600,000,000 Austin Hormel Foods
251 55426 45 -93 25,451 POINT (-93.38139 44.95635) Minnesota 1269900 802,600,000,000 Minneapolis General Mills
252 55423 45 -93 36,779 POINT (-93.28144 44.87663) Minnesota 1269900 802,600,000,000 Richfield Best Buy
253 72712 36 -94 38,072 POINT (-94.22196 36.39837) Arkansas 2283200 764,300,000,000 Bentonville Walmart
254 72745 36 -94 14,521 POINT (-94.10046 36.2477) Arkansas 2283200 764,300,000,000 Lowell J.B. Hunt Transport Services
255 72762 36 -94 47,402 POINT (-94.22794 36.18747) Arkansas 2283200 764,300,000,000 Springdale Tyson Foods
256 71730 33 -93 29,187 POINT (-92.63458 33.20303) Arkansas 2283200 764,300,000,000 El Dorado Murphy USA
257 23060 38 -78 36,111 POINT (-77.53427 37.65981) Virginia 1461200 738,400,000,000 Glen Allen Owens & Minor
258 23219 38 -77 3,856 POINT (-77.43484 37.54076) Virginia 1461200 738,400,000,000 Richmond Dominion Energy
259 23227 38 -77 25,574 POINT (-77.44234 37.61486) Virginia 1461200 738,400,000,000 Richmond ARKO
260 23230 38 -77 8,304 POINT (-77.49153 37.587) Virginia 1461200 738,400,000,000 Richmond Altria
261 23238 38 -78 25,893 POINT (-77.64138 37.59595) Virginia 1461200 738,400,000,000 Richmond Performance Food
262 22203 39 -77 25,921 POINT (-77.1164 38.87377) Virginia 1461200 738,400,000,000 Arlington AES
263 23238 38 -78 25,893 POINT (-77.64138 37.59595) Virginia 1461200 738,400,000,000 Richmond CarMax
264 23320 37 -76 59,626 POINT (-76.21807 36.75208) Virginia 1461200 738,400,000,000 Chesapeake Dollar Tree
265 23606 37 -76 29,899 POINT (-76.49557 37.07847) Virginia 1461200 738,400,000,000 Newport News Ferguson
266 23607 37 -76 23,028 POINT (-76.42235 36.98753) Virginia 1461200 738,400,000,000 Newport News Huntington Ingalls Industries
267 22209 39 -77 13,725 POINT (-77.07309 38.89413) Virginia 1461200 738,400,000,000 Arlington RTX
268 23060 38 -78 36,111 POINT (-77.53427 37.65981) Virginia 1461200 738,400,000,000 Glen Allen Markel
269 20190 39 -77 22,092 POINT (-77.33806 38.95968) Virginia 1461200 738,400,000,000 Reston CACI International
270 20190 39 -77 22,092 POINT (-77.33806 38.95968) Virginia 1461200 738,400,000,000 Reston General Dynamics
271 22102 39 -77 28,577 POINT (-77.22901 38.95199) Virginia 1461200 738,400,000,000 McLean Booz Allen Hamilton
272 22102 39 -77 28,577 POINT (-77.22901 38.95199) Virginia 1461200 738,400,000,000 McLean Hilton
273 22102 39 -77 28,577 POINT (-77.22901 38.95199) Virginia 1461200 738,400,000,000 McLean Capital One
274 22102 39 -77 28,577 POINT (-77.22901 38.95199) Virginia 1461200 738,400,000,000 McLean Freddie Mac
275 22042 39 -77 34,631 POINT (-77.19406 38.86463) Virginia 1461200 738,400,000,000 Falls Church Northrop Grumman
276 20190 39 -77 22,092 POINT (-77.33806 38.95968) Virginia 1461200 738,400,000,000 Reston Science Applications International
277 20190 39 -77 22,092 POINT (-77.33806 38.95968) Virginia 1461200 738,400,000,000 Reston NVR
278 20190 39 -77 22,092 POINT (-77.33806 38.95968) Virginia 1461200 738,400,000,000 Reston Leidos s
279 20170 39 -77 43,372 POINT (-77.38042 38.98075) Virginia 1461200 738,400,000,000 Herndon QXO Building Products
280 20147 39 -77 67,007 POINT (-77.47958 39.04151) Virginia 1461200 738,400,000,000 Ashburn DXC Technology
281 22202 39 -77 27,352 POINT (-77.05175 38.8569) Virginia 1461200 738,400,000,000 Arlington Boeing
282 15219 40 -80 11,010 POINT (-79.98443 40.44304) Pennsylvania 929200 672,400,000,000 Pittsburgh WESCO International
283 15317 40 -80 43,813 POINT (-80.16535 40.27105) Pennsylvania 929200 672,400,000,000 Canonsburg Viatris
284 15222 40 -80 5,649 POINT (-79.9912 40.44998) Pennsylvania 929200 672,400,000,000 Pittsburgh PNC
285 15219 40 -80 11,010 POINT (-79.98443 40.44304) Pennsylvania 929200 672,400,000,000 Pittsburgh United States Steel
286 15212 40 -80 27,600 POINT (-80.00844 40.47106) Pennsylvania 929200 672,400,000,000 Pittsburgh Alcoa
287 15212 40 -80 27,600 POINT (-80.00844 40.47106) Pennsylvania 929200 672,400,000,000 Pittsburgh Howmet Aerospace
288 15212 40 -80 27,600 POINT (-80.00844 40.47106) Pennsylvania 929200 672,400,000,000 Pittsburgh Westinghouse Air Brake Technologies
289 18101 41 -75 5,789 POINT (-75.4698 40.60301) Pennsylvania 929200 672,400,000,000 Allentown PPL
290 17033 40 -77 17,009 POINT (-76.62754 40.26829) Pennsylvania 929200 672,400,000,000 Hershey Hershey
291 19103 40 -75 25,602 POINT (-75.17386 39.95303) Pennsylvania 929200 672,400,000,000 Philadelphia Aramark
292 18106 41 -76 6,437 POINT (-75.59542 40.57472) Pennsylvania 929200 672,400,000,000 Allentown Air Products & Chemicals
293 19034 40 -75 7,084 POINT (-75.20953 40.13353) Pennsylvania 929200 672,400,000,000 Fort Washington Toll Brothers
294 19087 40 -75 33,770 POINT (-75.40004 40.06172) Pennsylvania 929200 672,400,000,000 Radnor Lincoln National
295 16530 42 -80 94,831 POINT (-80.08204 42.13039) Pennsylvania 929200 672,400,000,000 Erie Erie Insurance
296 15272 40 -80 2,481 POINT (-80.0048 40.44246) Pennsylvania 929200 672,400,000,000 Pittsburgh PPG Industries
297 19103 40 -75 25,602 POINT (-75.17386 39.95303) Pennsylvania 929200 672,400,000,000 Philadelphia Comcast
298 19406 40 -75 29,388 POINT (-75.38402 40.09467) Pennsylvania 929200 672,400,000,000 King of Prussia Universal Health Services
299 19428 40 -75 20,225 POINT (-75.30317 40.08011) Pennsylvania 929200 672,400,000,000 Conshohocken Cencora
300 15108 41 -80 42,782 POINT (-80.20031 40.50006) Pennsylvania 929200 672,400,000,000 Coraopolis Dick's Sporting Goods
In [139]:
musmaxrevst10 = gdfstsusmaxrevst10.explore(column='Revenue (rounded)', name='The Biggest Revenue State in US visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactusmaxrevst10.explore(m=musmaxrevst10, column='Revenue (rounded)', name='The Biggest Revenue State in US visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(musmaxrevst10)
musmaxrevst10
Out[139]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [140]:
# The Biggest Employer City in US (other viewpoint)
dfusmaxempct = df.groupby(['State','City'], as_index=False).sum('Employees').sort_values('Employees', ascending=False).reset_index(drop=True)
dfusmaxempct10 = dfusmaxempct.head(10)
dfusmaxempct
Out[140]:
State City Employees Revenue (rounded)
0 Washington Seattle 2101600 744,900,000,000
1 Arkansas Bentonville 2100000 681,000,000,000
2 New York New York 2028200 1,820,500,000,000
3 Georgia Atlanta 1233700 489,700,000,000
4 Illinois Chicago 724600 368,100,000,000
5 Ohio Cincinnati 593500 276,100,000,000
6 Texas Dallas 590100 366,500,000,000
7 Minnesota Minneapolis 573300 211,400,000,000
8 Tennessee Memphis 559900 124,800,000,000
9 Texas Houston 557600 906,500,000,000
10 California San Francisco 492000 296,000,000,000
11 Nebraska Omaha 463100 427,000,000,000
12 California Newark 450000 9,600,000,000
13 Pennsylvania Philadelphia 448700 141,100,000,000
14 North Carolina Charlotte 422700 331,300,000,000
15 Minnesota Eden Prairie 413800 418,000,000,000
16 Virginia Arlington 367100 159,500,000,000
17 Massachusetts Framingham 364000 56,400,000,000
18 New York Purchase 354300 120,100,000,000
19 New Jersey Teaneck 336800 19,700,000,000
20 Washington Issaquah 333000 254,500,000,000
21 Illinois Deerfield 290500 162,800,000,000
22 Texas Irving 287000 462,000,000,000
23 Texas Austin 284700 150,700,000,000
24 New York Armonk 284500 62,800,000,000
25 Maryland Bethesda 276000 96,100,000,000
26 Virginia McLean 275900 197,900,000,000
27 Tennessee Nashville 271000 70,600,000,000
28 Rhode Island Woonsocket 259500 372,800,000,000
29 Florida Lakeland 255000 60,200,000,000
30 California Santa Clara 250200 255,600,000,000
31 California San Jose 248200 153,000,000,000
32 Texas Plano 245500 11,300,000,000
33 Idaho Boise 244600 104,300,000,000
34 Washington Redmond 228000 245,100,000,000
35 Connecticut Stamford 225500 132,500,000,000
36 Virginia Reston 220000 90,300,000,000
37 North Carolina Mooresville 215500 83,700,000,000
38 Pennsylvania Pittsburgh 209800 119,200,000,000
39 California Mountain View 207500 366,300,000,000
40 California Burbank 205000 91,400,000,000
41 Tennessee Goodlettsville 194200 40,600,000,000
42 Florida Orlando 191100 11,400,000,000
43 Ohio Cleveland 188400 79,300,000,000
44 Michigan Detroit 182200 216,300,000,000
45 Connecticut Greenwich 179600 42,800,000,000
46 Michigan Southfield 173700 23,300,000,000
47 Indiana Indianapolis 172700 238,900,000,000
48 Michigan Dearborn 171000 185,000,000,000
49 California Cupertino 164000 391,000,000,000
50 Missouri St. Louis 160700 207,500,000,000
51 Florida St. Petersburg 157000 43,800,000,000
52 Virginia Chesapeake 139600 30,800,000,000
53 New Jersey New Brunswick 138100 88,800,000,000
54 Arkansas Springdale 138000 53,300,000,000
55 California Newport Beach 134800 27,100,000,000
56 Kentucky Louisville 134400 136,600,000,000
57 Texas Fort Worth 133300 54,200,000,000
58 Virginia Ashburn 130000 13,700,000,000
59 Massachusetts Waltham 128800 60,100,000,000
60 Connecticut Wallingford 125000 15,200,000,000
61 Colorado Denver 123800 51,200,000,000
62 Texas Spring 121900 379,700,000,000
63 Arizona Phoenix 121000 73,000,000,000
64 Massachusetts Boston 115500 106,400,000,000
65 Minnesota St. Paul 115100 48,500,000,000
66 Florida Jacksonville 114900 71,700,000,000
67 Illinois Abbott Park 114000 42,000,000,000
68 Nevada Las Vegas 109100 28,500,000,000
69 Texas Round Rock 108000 95,600,000,000
70 California Dublin 107000 21,100,000,000
71 Wisconsin Milwaukee 106900 96,700,000,000
72 Michigan Auburn Hills 100600 24,500,000,000
73 Virginia Richmond 99300 127,000,000,000
74 Virginia Falls Church 97000 41,000,000,000
75 California Palo Alto 95000 106,000,000,000
76 District of Columbia Washington 93200 185,200,000,000
77 North Carolina Durham 88000 15,400,000,000
78 Pennsylvania King of Prussia 87500 15,800,000,000
79 Massachusetts Marlborough 86000 37,200,000,000
80 Missouri Springfield 85600 16,700,000,000
81 Minnesota Richfield 85000 41,500,000,000
82 Massachusetts Cambridge 84400 44,600,000,000
83 Florida Coral Gables 82700 24,900,000,000
84 Ohio Akron 80300 31,900,000,000
85 Rhode Island Providence 79600 57,100,000,000
86 Oregon Beaverton 79400 51,400,000,000
87 Virginia Newport News 79000 41,100,000,000
88 California San Diego 74800 64,600,000,000
89 California Menlo Park 74100 164,500,000,000
90 New Jersey Rahway 74000 64,200,000,000
91 New Jersey Franklin Lakes 74000 20,200,000,000
92 Connecticut Bloomfield 72400 247,100,000,000
93 Connecticut Farmington 72000 14,300,000,000
94 Indiana Columbus 69600 34,100,000,000
95 Illinois Bloomington 67400 123,000,000,000
96 Ohio Mayfield Village 66300 75,400,000,000
97 North Carolina Burlington 65400 13,000,000,000
98 North Carolina Raleigh 65300 25,900,000,000
99 Connecticut Norwalk 64600 38,300,000,000
100 New Jersey Roseland 64000 19,200,000,000
101 Wisconsin Menomonee Falls 60000 16,200,000,000
102 Ohio Columbus 58700 90,300,000,000
103 New York Corning 56300 13,100,000,000
104 Illinois Rolling Meadows 56000 11,600,000,000
105 Illinois Moline 55500 51,700,000,000
106 Illinois Northbrook 55200 64,100,000,000
107 Illinois North Chicago 55000 56,300,000,000
108 Missouri Des Peres 55000 16,300,000,000
109 Ohio Evendale 53000 38,700,000,000
110 Michigan Portage 53000 22,600,000,000
111 Tennessee Franklin 52500 12,600,000,000
112 New Jersey Newark 50900 80,700,000,000
113 New Jersey Secaucus 50500 9,900,000,000
114 Nevada Reno 50000 11,300,000,000
115 Washington Bellevue 49000 44,300,000,000
116 Connecticut New Britain 48500 15,400,000,000
117 Ohio Dublin 48400 226,800,000,000
118 Florida Palm Beach Gardens 48000 24,800,000,000
119 Texas San Antonio 47900 172,600,000,000
120 New Jersey Burlington 47300 10,600,000,000
121 Tennessee Antioch 47000 14,400,000,000
122 Florida Melbourne 47000 21,300,000,000
123 Virginia Glen Allen 45200 27,300,000,000
124 Pennsylvania Conshohocken 44000 294,000,000,000
125 Michigan Benton Harbor 44000 16,600,000,000
126 Illinois Glenview 44000 15,900,000,000
127 California Fremont 43200 73,400,000,000
128 Indiana Evansville 42000 12,300,000,000
129 Georgia Calhoun 41900 10,800,000,000
130 Ohio Maumee 41900 21,600,000,000
131 Tennessee Brentwood 41000 27,400,000,000
132 Illinois Lake Forest 40400 25,600,000,000
133 California Oakland 39800 48,500,000,000
134 Georgia Duluth 39000 28,900,000,000
135 Illinois Bolingbrook 39000 11,300,000,000
136 Washington Sumner 39000 10,600,000,000
137 New Jersey Parsippany 38200 54,200,000,000
138 Pennsylvania Coraopolis 37400 13,400,000,000
139 Florida Tampa 36800 22,900,000,000
140 Arizona Chandler 36600 16,300,000,000
141 Michigan Midland 36000 43,000,000,000
142 Ohio Mentor 35000 8,800,000,000
143 California Beverly Hills 34200 30,700,000,000
144 New Jersey Princeton 34100 48,300,000,000
145 Arkansas Lowell 33600 12,100,000,000
146 Iowa Ankeny 33100 14,900,000,000
147 Colorado Englewood 32700 25,800,000,000
148 Texas Westlake 32100 26,000,000,000
149 Pennsylvania Canonsburg 32000 14,700,000,000
150 Alabama Birmingham 31600 16,800,000,000
151 Ohio Westerville 31000 8,000,000,000
152 New York Long Island City 30700 18,300,000,000
153 Oregon Medford 30200 36,600,000,000
154 Illinois Rosemont 30000 37,900,000,000
155 Massachusetts Burlington 29400 15,400,000,000
156 Pennsylvania Allentown 29100 20,600,000,000
157 Michigan Bloomfield Hills 28900 30,500,000,000
158 California Thousand Oaks 28000 33,400,000,000
159 California Redwood City 27300 16,300,000,000
160 California Irvine 26100 48,000,000,000
161 Florida Estero 26000 9,000,000,000
162 Ohio Toledo 25700 19,000,000,000
163 Florida Miami 25300 85,200,000,000
164 Florida Fort Lauderdale 25100 26,800,000,000
165 Louisiana Monroe 25000 13,100,000,000
166 New York Melville 25000 12,700,000,000
167 Delaware Wilmington 24000 12,400,000,000
168 Illinois Downers Grove 24000 8,400,000,000
169 Massachusetts Wilmington 24000 9,400,000,000
170 Indiana Elkhart 22300 10,000,000,000
171 New York Buffalo 22100 13,500,000,000
172 Minnesota Maplewood 22000 8,300,000,000
173 New Jersey Summit 22000 15,500,000,000
174 Massachusetts Springfield 21900 55,000,000,000
175 Colorado Centennial 21500 27,900,000,000
176 Illinois Riverwoods 21000 23,600,000,000
177 Minnesota Winona 21000 7,500,000,000
178 California Pleasanton 20500 8,400,000,000
179 Minnesota Austin 20000 11,900,000,000
180 Iowa Des Moines 19700 16,100,000,000
181 Pennsylvania Hershey 19300 11,200,000,000
182 Connecticut Hartford 19100 26,500,000,000
183 Arizona Scottsdale 19000 22,000,000,000
184 Wisconsin Oshkosh 18500 10,700,000,000
185 Ohio Findlay 18300 140,400,000,000
186 California Long Beach 18000 40,600,000,000
187 Florida Plantation 18000 11,900,000,000
188 Michigan Livonia 18000 7,800,000,000
189 California Foster City 17600 28,800,000,000
190 Arizona Tempe 17400 13,700,000,000
191 Indiana Warsaw 17000 7,700,000,000
192 Florida Juno Beach 16800 24,800,000,000
193 Colorado Westminster 16000 12,100,000,000
194 California Sunnyvale 15600 8,400,000,000
195 California Manhattan Beach 15100 9,000,000,000
196 Illinois Vernon Hills 15100 21,000,000,000
197 California Milpitas 15100 9,800,000,000
198 New York Tarrytown 15100 14,200,000,000
199 Michigan Byron Center 15000 9,500,000,000
200 Florida Sunny Isles Beach 15000 10,000,000,000
201 Texas Arlington 14800 36,800,000,000
202 New Jersey Camden 14400 9,600,000,000
203 Maryland Baltimore 14200 23,600,000,000
204 Tennessee Kingsport 14000 9,400,000,000
205 California Rosemead 14000 17,600,000,000
206 Kansas Merriam 14000 9,100,000,000
207 California Los Gatos 14000 39,000,000,000
208 Indiana Fort Wayne 13000 17,500,000,000
209 Georgia Columbus 12700 18,900,000,000
210 Illinois Oak Brook 12500 9,500,000,000
211 Louisiana New Orleans 12300 11,900,000,000
212 Arkansas El Dorado 11600 17,900,000,000
213 Illinois Westchester 11200 7,400,000,000
214 Wisconsin Madison 11100 21,300,000,000
215 Oklahoma Tulsa 11000 32,200,000,000
216 Tennessee Chattanooga 10900 12,900,000,000
217 Minnesota Inver Grove Heights 10700 39,300,000,000
218 California San Mateo 10200 8,500,000,000
219 California Woodland Hills 9900 15,500,000,000
220 Pennsylvania Radnor 9800 18,400,000,000
221 New York Victor 9300 10,000,000,000
222 Ohio Orrville 9000 8,200,000,000
223 Minnesota Arden Hills 9000 16,200,000,000
224 Michigan Jackson 8300 7,500,000,000
225 Virginia Herndon 8100 9,800,000,000
226 Texas New Braunfels 7900 7,800,000,000
227 Michigan Lansing 7300 15,800,000,000
228 Pennsylvania Erie 6700 13,200,000,000
229 California Corona 6000 7,500,000,000
230 Rhode Island Johnston 5800 10,400,000,000
231 Ohio Fairfield 5600 11,300,000,000
232 Pennsylvania Fort Washington 4900 10,800,000,000
233 Missouri Chesterfield 4100 22,100,000,000
234 Oklahoma Oklahoma City 2300 15,900,000,000
235 Texas Midland 2000 11,100,000,000
236 California El Segundo 500 9,700,000,000
In [141]:
dfusmaxempct10 = dfusmaxempct10.merge(df[['State','City','Company','Zip Code']], how = 'inner', on = ['State','City'])

gdfstsusmaxempct10 = gdfsts.merge(dfusmaxempct10, how = 'inner', on = ['State'])
gdfusactusmaxempct10 = gdfusact.merge(dfusmaxempct10, how = 'inner', on = ['Zip Code']).sort_values('Employees', ascending=False).reset_index(drop=True)
gdfusactusmaxempct10
gdfstsusmaxempct10
Out[141]:
State region postal latitude longitude geometry City Employees Revenue (rounded) Company Zip Code
0 Minnesota Midwest MN 46 -93 POLYGON ((-89.95766 47.28691, -90.13175 47.292... Minneapolis 573300 211,400,000,000 Target 55403
1 Minnesota Midwest MN 46 -93 POLYGON ((-89.95766 47.28691, -90.13175 47.292... Minneapolis 573300 211,400,000,000 U.S. Bancorp 55402
2 Minnesota Midwest MN 46 -93 POLYGON ((-89.95766 47.28691, -90.13175 47.292... Minneapolis 573300 211,400,000,000 General Mills 55426
3 Minnesota Midwest MN 46 -93 POLYGON ((-89.95766 47.28691, -90.13175 47.292... Minneapolis 573300 211,400,000,000 Ameriprise Financial 55474
4 Minnesota Midwest MN 46 -93 POLYGON ((-89.95766 47.28691, -90.13175 47.292... Minneapolis 573300 211,400,000,000 Xcel Energy 55401
5 Minnesota Midwest MN 46 -93 POLYGON ((-89.95766 47.28691, -90.13175 47.292... Minneapolis 573300 211,400,000,000 Thrivent Financial for Lutherans 55415
6 Washington West WA 47 -120 POLYGON ((-117.03143 48.99931, -117.02665 47.7... Seattle 2101600 744,900,000,000 Amazon 98109
7 Washington West WA 47 -120 POLYGON ((-117.03143 48.99931, -117.02665 47.7... Seattle 2101600 744,900,000,000 Starbucks 98134
8 Washington West WA 47 -120 POLYGON ((-117.03143 48.99931, -117.02665 47.7... Seattle 2101600 744,900,000,000 Coupang 98101
9 Washington West WA 47 -120 POLYGON ((-117.03143 48.99931, -117.02665 47.7... Seattle 2101600 744,900,000,000 Nordstrom 98101
10 Washington West WA 47 -120 POLYGON ((-117.03143 48.99931, -117.02665 47.7... Seattle 2101600 744,900,000,000 Expedia 98119
11 Washington West WA 47 -120 POLYGON ((-117.03143 48.99931, -117.02665 47.7... Seattle 2101600 744,900,000,000 Alaska Air 98188
12 Arkansas South AR 35 -92 POLYGON ((-89.66292 36.02307, -89.67351 35.94,... Bentonville 2100000 681,000,000,000 Walmart 72712
13 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Dallas 590100 366,500,000,000 AT&T 75202
14 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Dallas 590100 366,500,000,000 Energy Transfer 75225
15 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Dallas 590100 366,500,000,000 CBRE 75201
16 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Dallas 590100 366,500,000,000 HF Sinclair 75219
17 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Dallas 590100 366,500,000,000 Southwest Airlines 75235
18 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Dallas 590100 366,500,000,000 Tenet Healthcare 75254
19 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Dallas 590100 366,500,000,000 Jacobs Solutions 75201
20 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Dallas 590100 366,500,000,000 AECOM 75240
21 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Dallas 590100 366,500,000,000 Texas Instruments 75243
22 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 Chevron 77002
23 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 Phillips 66 77042
24 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 Sysco 77077
25 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 ConocoPhillips 77079
26 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 Enterprise Products Partners 77002
27 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 Plains GP 77002
28 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 NRG Energy 77002
29 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 Baker Hughes 77079
30 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 Occidental Petroleum 77046
31 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 EOG Resources 77002
32 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 Quanta Services 77008
33 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 Halliburton 77032
34 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 Waste Management 77002
35 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 1 Automotive 77024
36 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 Corebridge Financial 77019
37 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 Targa Resources 77002
38 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 Cheniere Energy 77002
39 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 Kinder Morgan 77002
40 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 Westlake 77056
41 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 APA 77042
42 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 NOV 77042
43 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 CenterPoint Energy 77002
44 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 Par Pacific 77024
45 Texas South TX 31 -99 POLYGON ((-106.50734 31.75429, -106.61953 31.9... Houston 557600 906,500,000,000 KBR 77002
46 Georgia South GA 33 -83 POLYGON ((-85.00519 30.99069, -85.05442 31.108... Atlanta 1233700 489,700,000,000 Home Depot 30339
47 Georgia South GA 33 -83 POLYGON ((-85.00519 30.99069, -85.05442 31.108... Atlanta 1233700 489,700,000,000 UPS 30328
48 Georgia South GA 33 -83 POLYGON ((-85.00519 30.99069, -85.05442 31.108... Atlanta 1233700 489,700,000,000 Delta Airlines 30354
49 Georgia South GA 33 -83 POLYGON ((-85.00519 30.99069, -85.05442 31.108... Atlanta 1233700 489,700,000,000 Coca-Cola 30313
50 Georgia South GA 33 -83 POLYGON ((-85.00519 30.99069, -85.05442 31.108... Atlanta 1233700 489,700,000,000 Southern 30308
51 Georgia South GA 33 -83 POLYGON ((-85.00519 30.99069, -85.05442 31.108... Atlanta 1233700 489,700,000,000 Genuine Parts 30339
52 Georgia South GA 33 -83 POLYGON ((-85.00519 30.99069, -85.05442 31.108... Atlanta 1233700 489,700,000,000 Pulte 30326
53 Georgia South GA 33 -83 POLYGON ((-85.00519 30.99069, -85.05442 31.108... Atlanta 1233700 489,700,000,000 Norfolk Southern 30308
54 Georgia South GA 33 -83 POLYGON ((-85.00519 30.99069, -85.05442 31.108... Atlanta 1233700 489,700,000,000 Assurant 30339
55 Georgia South GA 33 -83 POLYGON ((-85.00519 30.99069, -85.05442 31.108... Atlanta 1233700 489,700,000,000 Intercontinental Exchange 30328
56 Georgia South GA 33 -83 POLYGON ((-85.00519 30.99069, -85.05442 31.108... Atlanta 1233700 489,700,000,000 Global Payments 30326
57 Georgia South GA 33 -83 POLYGON ((-85.00519 30.99069, -85.05442 31.108... Atlanta 1233700 489,700,000,000 Graphic Packaging 30328
58 Georgia South GA 33 -83 POLYGON ((-85.00519 30.99069, -85.05442 31.108... Atlanta 1233700 489,700,000,000 Newell Brands 30328
59 Illinois Midwest IL 40 -89 POLYGON ((-91.43033 40.3686, -91.41023 40.5511... Chicago 724600 368,100,000,000 Archer Daniels Midland 60601
60 Illinois Midwest IL 40 -89 POLYGON ((-91.43033 40.3686, -91.41023 40.5511... Chicago 724600 368,100,000,000 United Airlines 60606
61 Illinois Midwest IL 40 -89 POLYGON ((-91.43033 40.3686, -91.41023 40.5511... Chicago 724600 368,100,000,000 Mondelez 60607
62 Illinois Midwest IL 40 -89 POLYGON ((-91.43033 40.3686, -91.41023 40.5511... Chicago 724600 368,100,000,000 McDonald's 60607
63 Illinois Midwest IL 40 -89 POLYGON ((-91.43033 40.3686, -91.41023 40.5511... Chicago 724600 368,100,000,000 Kraft Heinz 60601
64 Illinois Midwest IL 40 -89 POLYGON ((-91.43033 40.3686, -91.41023 40.5511... Chicago 724600 368,100,000,000 Jones Lang LaSalle 60601
65 Illinois Midwest IL 40 -89 POLYGON ((-91.43033 40.3686, -91.41023 40.5511... Chicago 724600 368,100,000,000 Exelon 60603
66 Illinois Midwest IL 40 -89 POLYGON ((-91.43033 40.3686, -91.41023 40.5511... Chicago 724600 368,100,000,000 GE HealthCare Technologies 60661
67 Illinois Midwest IL 40 -89 POLYGON ((-91.43033 40.3686, -91.41023 40.5511... Chicago 724600 368,100,000,000 Northern Trust 60603
68 Illinois Midwest IL 40 -89 POLYGON ((-91.43033 40.3686, -91.41023 40.5511... Chicago 724600 368,100,000,000 Kellanova 60654
69 Illinois Midwest IL 40 -89 POLYGON ((-91.43033 40.3686, -91.41023 40.5511... Chicago 724600 368,100,000,000 Conagra Brands 60654
70 Illinois Midwest IL 40 -89 POLYGON ((-91.43033 40.3686, -91.41023 40.5511... Chicago 724600 368,100,000,000 Molson Coors Beverage 60606
71 Illinois Midwest IL 40 -89 POLYGON ((-91.43033 40.3686, -91.41023 40.5511... Chicago 724600 368,100,000,000 Motorola Solutions 60661
72 Illinois Midwest IL 40 -89 POLYGON ((-91.43033 40.3686, -91.41023 40.5511... Chicago 724600 368,100,000,000 Old Republic International 60601
73 Ohio Midwest OH 40 -83 POLYGON ((-84.82368 39.10653, -84.81787 39.799... Cincinnati 593500 276,100,000,000 Kroger 45202
74 Ohio Midwest OH 40 -83 POLYGON ((-84.82368 39.10653, -84.81787 39.799... Cincinnati 593500 276,100,000,000 Procter & Gamble 45202
75 Ohio Midwest OH 40 -83 POLYGON ((-84.82368 39.10653, -84.81787 39.799... Cincinnati 593500 276,100,000,000 Western & Southern Financial 45202
76 Ohio Midwest OH 40 -83 POLYGON ((-84.82368 39.10653, -84.81787 39.799... Cincinnati 593500 276,100,000,000 Fifth Third Bancorp 45263
77 Ohio Midwest OH 40 -83 POLYGON ((-84.82368 39.10653, -84.81787 39.799... Cincinnati 593500 276,100,000,000 Cintas 45262
78 Ohio Midwest OH 40 -83 POLYGON ((-84.82368 39.10653, -84.81787 39.799... Cincinnati 593500 276,100,000,000 American Financial 45202
79 Tennessee South TN 36 -86 POLYGON ((-90.24924 35.02083, -90.13493 35.113... Memphis 559900 124,800,000,000 FedEx 38120
80 Tennessee South TN 36 -86 POLYGON ((-90.24924 35.02083, -90.13493 35.113... Memphis 559900 124,800,000,000 International Paper 38197
81 Tennessee South TN 36 -86 POLYGON ((-90.24924 35.02083, -90.13493 35.113... Memphis 559900 124,800,000,000 AutoZone 38103
82 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 JPMorgan Chase 10017
83 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Citi 10013
84 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Verizon 10036
85 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Goldman Sachs 10282
86 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Morgan Stanley 10036
87 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 StoneX 10169
88 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 American Express 10285
89 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 MetLife 10166
90 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Pfizer 10001
91 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 New York Life Insurance 10010
92 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 TIAA 10017
93 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Travelers 10017
94 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Bank of New York 10286
95 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Warner Bros. Discovery 10003
96 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 KKR 10001
97 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Paramount Global 10036
98 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 American International 10020
99 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Apollo Global Management 10019
100 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Marsh & McLennan 10036
101 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Macy's 10001
102 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 BlackRock 10001
103 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Colgate-Palmolive 10022
104 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Loews 10019
105 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Guardian Life 10001
106 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Kyndryl s 10017
107 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Omnicom 10017
108 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Estée Lauder 10153
109 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Consolidated Edison 10003
110 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 S&P Global 10041
111 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Fox 10036
112 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Blackstone 10154
113 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Hess 10036
114 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Equitable 10105
115 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 International Flavors & Fragrances 10019
116 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Interpublic 10022
117 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Jefferies Financial 10022
118 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 News Corp. 10036
119 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Oscar Health 10013
120 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Sirius XM 10020
121 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 PVH 10017
122 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 ABM Industries 10006
123 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Voya Financial 10169
124 New York Northeast NY 43 -75 POLYGON ((-73.49794 42.05451, -73.55349 41.289... New York 2028200 1,820,500,000,000 Foot Locker 10001
In [142]:
musmaxempct10 = gdfstsusmaxempct10.explore(column='Employees', name='The Biggest Employer City in US visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactusmaxempct10.explore(m=musmaxempct10, column='Employees', name='The Biggest Employer City in US visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(musmaxempct10)
musmaxempct10
Out[142]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [143]:
# The Biggest Employer State in US (other viewpoint)
dfusmaxempst = df.groupby(['State'], as_index=False).sum('Employees').sort_values('Employees', ascending=False).reset_index(drop=True)
dfusmaxempst10 = dfusmaxempst.head(10)
dfusmaxempst
Out[143]:
State Employees Revenue (rounded)
0 California 2857700 2,399,300,000,000
1 New York 2825500 2,085,200,000,000
2 Washington 2750600 1,299,400,000,000
3 Texas 2432800 2,680,800,000,000
4 Arkansas 2283200 764,300,000,000
5 Illinois 1655400 1,040,200,000,000
6 Virginia 1461200 738,400,000,000
7 Georgia 1327300 548,300,000,000
8 Minnesota 1269900 802,600,000,000
9 Ohio 1255100 1,035,800,000,000
10 Tennessee 1190500 312,700,000,000
11 Florida 1058700 448,700,000,000
12 New Jersey 944300 440,900,000,000
13 Pennsylvania 929200 672,400,000,000
14 North Carolina 856900 469,300,000,000
15 Massachusetts 854000 384,500,000,000
16 Michigan 838000 602,400,000,000
17 Connecticut 806700 532,100,000,000
18 Nebraska 463100 427,000,000,000
19 Rhode Island 344900 440,300,000,000
20 Indiana 336600 320,500,000,000
21 Missouri 305400 262,600,000,000
22 Maryland 290200 119,700,000,000
23 Idaho 244600 104,300,000,000
24 Wisconsin 196500 144,900,000,000
25 Arizona 194000 125,000,000,000
26 Colorado 194000 117,000,000,000
27 Nevada 159100 39,800,000,000
28 Kentucky 134400 136,600,000,000
29 Oregon 109600 88,000,000,000
30 District of Columbia 93200 185,200,000,000
31 Iowa 52800 31,000,000,000
32 Louisiana 37300 25,000,000,000
33 Alabama 31600 16,800,000,000
34 Delaware 24000 12,400,000,000
35 Kansas 14000 9,100,000,000
36 Oklahoma 13300 48,100,000,000
In [144]:
dfusmaxempst10 = dfusmaxempst10.merge(df[['State','City','Company','Zip Code']], how = 'inner', on = ['State'])

gdfstsusmaxempst10 = gdfsts.merge(dfusmaxempst10, how = 'inner', on = ['State'])
gdfusactusmaxempst10 = gdfusact.merge(dfusmaxempst10, how = 'inner', on = ['Zip Code']).sort_values('Employees', ascending=False).reset_index(drop=True)
gdfusactusmaxempst10
Out[144]:
Zip Code Latitude Longitude Population geometry State Employees Revenue (rounded) City Company
0 91521 34 -118 11,049 POINT (-118.3252 34.1569) California 2857700 2,399,300,000,000 Burbank Walt Disney
1 94304 37 -122 4,731 POINT (-122.16699 37.39744) California 2857700 2,399,300,000,000 Palo Alto Broadcom
2 94158 38 -122 11,206 POINT (-122.39153 37.77116) California 2857700 2,399,300,000,000 San Francisco Uber
3 94111 38 -122 4,553 POINT (-122.3998 37.79847) California 2857700 2,399,300,000,000 San Francisco Prologis
4 94109 38 -122 54,397 POINT (-122.42138 37.79334) California 2857700 2,399,300,000,000 San Francisco Williams-Sonoma
5 94107 38 -122 30,190 POINT (-122.39508 37.76473) California 2857700 2,399,300,000,000 San Francisco DoorDash
6 94105 38 -122 14,890 POINT (-122.39707 37.79239) California 2857700 2,399,300,000,000 San Francisco Gap
7 94105 38 -122 14,890 POINT (-122.39707 37.79239) California 2857700 2,399,300,000,000 San Francisco Visa
8 94105 38 -122 14,890 POINT (-122.39707 37.79239) California 2857700 2,399,300,000,000 San Francisco Salesforce
9 94104 38 -122 478 POINT (-122.40211 37.79144) California 2857700 2,399,300,000,000 San Francisco Wells Fargo
10 94103 38 -122 33,524 POINT (-122.41136 37.77299) California 2857700 2,399,300,000,000 San Francisco Airbnb
11 94086 37 -122 48,956 POINT (-122.02316 37.37164) California 2857700 2,399,300,000,000 Sunnyvale Intuitive Surgical
12 94065 38 -122 11,620 POINT (-122.24683 37.53504) California 2857700 2,399,300,000,000 Redwood City Electronic Arts
13 94065 38 -122 11,620 POINT (-122.24683 37.53504) California 2857700 2,399,300,000,000 Redwood City Equinix
14 94043 37 -122 32,042 POINT (-122.06892 37.41188) California 2857700 2,399,300,000,000 Mountain View Intuit
15 94043 37 -122 32,042 POINT (-122.06892 37.41188) California 2857700 2,399,300,000,000 Mountain View Alphabet
16 94025 37 -122 40,230 POINT (-122.1829 37.45087) California 2857700 2,399,300,000,000 Menlo Park Meta
17 92879 34 -118 48,756 POINT (-117.5357 33.87979) California 2857700 2,399,300,000,000 Corona Monster Beverage
18 92660 34 -118 34,788 POINT (-117.87504 33.63375) California 2857700 2,399,300,000,000 Newport Beach Chipotle Mexican Grill
19 92660 34 -118 34,788 POINT (-117.87504 33.63375) California 2857700 2,399,300,000,000 Newport Beach Pacific Life
20 92612 34 -118 33,706 POINT (-117.82457 33.65984) California 2857700 2,399,300,000,000 Irvine Ingram Micro
21 92121 33 -117 4,157 POINT (-117.20231 32.8973) California 2857700 2,399,300,000,000 San Diego LPL Financial s
22 92121 33 -117 4,157 POINT (-117.20231 32.8973) California 2857700 2,399,300,000,000 San Diego Qualcomm
23 92101 33 -117 48,163 POINT (-117.18589 32.7162) California 2857700 2,399,300,000,000 San Diego Sempra
24 91770 34 -118 58,893 POINT (-118.08361 34.06395) California 2857700 2,399,300,000,000 Rosemead Edison International
25 91367 34 -119 45,427 POINT (-118.61518 34.17708) California 2857700 2,399,300,000,000 Woodland Hills Farmers Insurance Exchange
26 91320 34 -119 43,628 POINT (-118.94795 34.17339) California 2857700 2,399,300,000,000 Thousand Oaks Amgen
27 90802 34 -118 39,859 POINT (-118.21143 33.75035) California 2857700 2,399,300,000,000 Long Beach Molina Healthcare
28 90266 34 -118 34,584 POINT (-118.39705 33.88968) California 2857700 2,399,300,000,000 Manhattan Beach Skechers U.S.A.
29 90245 34 -118 16,863 POINT (-118.40161 33.91709) California 2857700 2,399,300,000,000 El Segundo A-Mark Precious Metals
30 90210 34 -118 19,652 POINT (-118.41505 34.10251) California 2857700 2,399,300,000,000 Beverly Hills Endeavor
31 94304 37 -122 4,731 POINT (-122.16699 37.39744) California 2857700 2,399,300,000,000 Palo Alto HP
32 94403 38 -122 43,459 POINT (-122.30454 37.53844) California 2857700 2,399,300,000,000 San Mateo Franklin Resources
33 95054 37 -122 25,196 POINT (-121.96483 37.39308) California 2857700 2,399,300,000,000 Santa Clara ServiceNow
34 95054 37 -122 25,196 POINT (-121.96483 37.39308) California 2857700 2,399,300,000,000 Santa Clara Intel
35 95134 37 -122 30,255 POINT (-121.94528 37.43003) California 2857700 2,399,300,000,000 San Jose Sanmina
36 95134 37 -122 30,255 POINT (-121.94528 37.43003) California 2857700 2,399,300,000,000 San Jose Cisco Systems
37 95131 37 -122 30,745 POINT (-121.89793 37.38729) California 2857700 2,399,300,000,000 San Jose Super Micro Computer
38 95131 37 -122 30,745 POINT (-121.89793 37.38729) California 2857700 2,399,300,000,000 San Jose PayPal
39 95125 37 -122 53,934 POINT (-121.89408 37.29554) California 2857700 2,399,300,000,000 San Jose Ebay
40 95119 37 -122 10,449 POINT (-121.79077 37.22756) California 2857700 2,399,300,000,000 San Jose Western Digital
41 95110 37 -122 19,444 POINT (-121.9097 37.34656) California 2857700 2,399,300,000,000 San Jose Adobe
42 95054 37 -122 25,196 POINT (-121.96483 37.39308) California 2857700 2,399,300,000,000 Santa Clara Palo Alto Networks
43 94404 38 -122 35,950 POINT (-122.26905 37.5562) California 2857700 2,399,300,000,000 Foster City Gilead Sciences
44 95054 37 -122 25,196 POINT (-121.96483 37.39308) California 2857700 2,399,300,000,000 Santa Clara Advanced Micro Devices
45 95054 37 -122 25,196 POINT (-121.96483 37.39308) California 2857700 2,399,300,000,000 Santa Clara Applied Materials
46 90210 34 -118 19,652 POINT (-118.41505 34.10251) California 2857700 2,399,300,000,000 Beverly Hills Live Nation Entertainment
47 95051 37 -122 61,345 POINT (-121.98444 37.3483) California 2857700 2,399,300,000,000 Santa Clara Nvidia
48 94588 38 -122 34,423 POINT (-121.88178 37.73801) California 2857700 2,399,300,000,000 Pleasanton Workday
49 94538 38 -122 67,704 POINT (-121.96361 37.50653) California 2857700 2,399,300,000,000 Fremont TD Synnex
50 95035 37 -122 78,479 POINT (-121.87632 37.44319) California 2857700 2,399,300,000,000 Milpitas KLA
51 94560 38 -122 47,145 POINT (-122.02523 37.50771) California 2857700 2,399,300,000,000 Newark Concentrix
52 94568 38 -122 70,542 POINT (-121.90113 37.71596) California 2857700 2,399,300,000,000 Dublin Ross Stores
53 94538 38 -122 67,704 POINT (-121.96361 37.50653) California 2857700 2,399,300,000,000 Fremont Lam Research
54 94612 38 -122 17,663 POINT (-122.2662 37.80789) California 2857700 2,399,300,000,000 Oakland PG&E
55 94612 38 -122 17,663 POINT (-122.2662 37.80789) California 2857700 2,399,300,000,000 Oakland Block
56 95014 37 -122 61,109 POINT (-122.07981 37.30827) California 2857700 2,399,300,000,000 Cupertino Apple
57 95032 37 -122 27,682 POINT (-121.92359 37.20859) California 2857700 2,399,300,000,000 Los Gatos Netflix
58 10041 41 -74 6,217 POINT (-74.01 40.7031) New York 2825500 2,085,200,000,000 New York S&P Global
59 10105 41 -74 0 POINT (-73.978 40.7644) New York 2825500 2,085,200,000,000 New York Equitable
60 10166 41 -74 0 POINT (-73.9769 40.7531) New York 2825500 2,085,200,000,000 New York MetLife
61 10285 41 -74 0 POINT (-74.01492 40.71201) New York 2825500 2,085,200,000,000 New York American Express
62 10286 41 -74 5,269 POINT (-74.01182 40.7052) New York 2825500 2,085,200,000,000 New York Bank of New York
63 14831 42 -77 5,986 POINT (-77.0553 42.1429) New York 2825500 2,085,200,000,000 Corning Corning
64 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York 2825500 2,085,200,000,000 New York KKR
65 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York 2825500 2,085,200,000,000 New York Pfizer
66 11101 41 -74 39,007 POINT (-73.93916 40.74679) New York 2825500 2,085,200,000,000 Long Island City Altice USA
67 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York 2825500 2,085,200,000,000 New York Omnicom
68 10019 41 -74 44,276 POINT (-73.9853 40.76586) New York 2825500 2,085,200,000,000 New York Apollo Global Management
69 10019 41 -74 44,276 POINT (-73.9853 40.76586) New York 2825500 2,085,200,000,000 New York Loews
70 10019 41 -74 44,276 POINT (-73.9853 40.76586) New York 2825500 2,085,200,000,000 New York International Flavors & Fragrances
71 10020 41 -74 0 POINT (-73.98071 40.75917) New York 2825500 2,085,200,000,000 New York American International
72 10020 41 -74 0 POINT (-73.98071 40.75917) New York 2825500 2,085,200,000,000 New York Sirius XM
73 10022 41 -74 34,340 POINT (-73.96787 40.75856) New York 2825500 2,085,200,000,000 New York Colgate-Palmolive
74 10022 41 -74 34,340 POINT (-73.96787 40.75856) New York 2825500 2,085,200,000,000 New York Interpublic
75 10022 41 -74 34,340 POINT (-73.96787 40.75856) New York 2825500 2,085,200,000,000 New York Jefferies Financial
76 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York 2825500 2,085,200,000,000 New York Verizon
77 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York 2825500 2,085,200,000,000 New York Paramount Global
78 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York 2825500 2,085,200,000,000 New York Marsh & McLennan
79 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York 2825500 2,085,200,000,000 New York Fox
80 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York 2825500 2,085,200,000,000 New York Hess
81 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York 2825500 2,085,200,000,000 New York News Corp.
82 10153 41 -74 0 POINT (-73.97244 40.76362) New York 2825500 2,085,200,000,000 New York Estée Lauder
83 10154 41 -74 0 POINT (-73.97249 40.75778) New York 2825500 2,085,200,000,000 New York Blackstone
84 10169 41 -74 0 POINT (-73.97643 40.75467) New York 2825500 2,085,200,000,000 New York StoneX
85 10169 41 -74 0 POINT (-73.97643 40.75467) New York 2825500 2,085,200,000,000 New York Voya Financial
86 10282 41 -74 5,960 POINT (-74.01495 40.71655) New York 2825500 2,085,200,000,000 New York Goldman Sachs
87 10504 41 -74 7,853 POINT (-73.70629 41.13065) New York 2825500 2,085,200,000,000 Armonk IBM
88 10577 41 -74 5,901 POINT (-73.71349 41.03755) New York 2825500 2,085,200,000,000 Purchase PepsiCo
89 10577 41 -74 5,901 POINT (-73.71349 41.03755) New York 2825500 2,085,200,000,000 Purchase Mastercard
90 10591 41 -74 23,663 POINT (-73.84653 41.08436) New York 2825500 2,085,200,000,000 Tarrytown Regeneron Pharmaceuticals
91 11101 41 -74 39,007 POINT (-73.93916 40.74679) New York 2825500 2,085,200,000,000 Long Island City JetBlue Airways
92 11747 41 -73 19,826 POINT (-73.40931 40.78372) New York 2825500 2,085,200,000,000 Melville Henry Schein
93 14203 43 -79 2,526 POINT (-78.86507 42.86244) New York 2825500 2,085,200,000,000 Buffalo M&T Bank
94 14564 43 -77 16,257 POINT (-77.42417 42.98329) New York 2825500 2,085,200,000,000 Victor Constellation Brands
95 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York 2825500 2,085,200,000,000 New York PVH
96 10036 41 -74 30,589 POINT (-73.99064 40.75976) New York 2825500 2,085,200,000,000 New York Morgan Stanley
97 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York 2825500 2,085,200,000,000 New York Kyndryl s
98 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York 2825500 2,085,200,000,000 New York TIAA
99 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York 2825500 2,085,200,000,000 New York JPMorgan Chase
100 10013 41 -74 28,215 POINT (-74.00472 40.72001) New York 2825500 2,085,200,000,000 New York Oscar Health
101 10013 41 -74 28,215 POINT (-74.00472 40.72001) New York 2825500 2,085,200,000,000 New York Citi
102 10010 41 -74 31,905 POINT (-73.98243 40.73899) New York 2825500 2,085,200,000,000 New York New York Life Insurance
103 10006 41 -74 4,475 POINT (-74.01306 40.70949) New York 2825500 2,085,200,000,000 New York ABM Industries
104 10017 41 -74 14,985 POINT (-73.9726 40.75235) New York 2825500 2,085,200,000,000 New York Travelers
105 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York 2825500 2,085,200,000,000 New York Macy's
106 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York 2825500 2,085,200,000,000 New York BlackRock
107 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York 2825500 2,085,200,000,000 New York Guardian Life
108 10001 41 -74 29,079 POINT (-73.99728 40.75064) New York 2825500 2,085,200,000,000 New York Foot Locker
109 10003 41 -74 53,825 POINT (-73.98915 40.73184) New York 2825500 2,085,200,000,000 New York Warner Bros. Discovery
110 10003 41 -74 53,825 POINT (-73.98915 40.73184) New York 2825500 2,085,200,000,000 New York Consolidated Edison
111 98134 48 -122 779 POINT (-122.33686 47.57691) Washington 2750600 1,299,400,000,000 Seattle Starbucks
112 98188 47 -122 26,769 POINT (-122.27398 47.44754) Washington 2750600 1,299,400,000,000 Seattle Alaska Air
113 98390 47 -122 11,497 POINT (-122.22894 47.21195) Washington 2750600 1,299,400,000,000 Sumner Lululemon athletica
114 98119 48 -122 26,390 POINT (-122.36932 47.63943) Washington 2750600 1,299,400,000,000 Seattle Expedia
115 98101 48 -122 16,396 POINT (-122.33454 47.61119) Washington 2750600 1,299,400,000,000 Seattle Nordstrom
116 98101 48 -122 16,396 POINT (-122.33454 47.61119) Washington 2750600 1,299,400,000,000 Seattle Coupang
117 98052 48 -122 79,074 POINT (-122.1203 47.68148) Washington 2750600 1,299,400,000,000 Redmond Microsoft
118 98027 48 -122 28,335 POINT (-122.00176 47.50387) Washington 2750600 1,299,400,000,000 Issaquah Costco
119 98006 48 -122 40,770 POINT (-122.14957 47.55772) Washington 2750600 1,299,400,000,000 Bellevue Expeditors International of Washington
120 98004 48 -122 39,435 POINT (-122.20548 47.61865) Washington 2750600 1,299,400,000,000 Bellevue Paccar
121 98109 48 -122 32,552 POINT (-122.34486 47.63128) Washington 2750600 1,299,400,000,000 Seattle Amazon
122 75038 33 -97 33,097 POINT (-96.97946 32.87231) Texas 2432800 2,680,800,000,000 Irving Kimberly-Clark
123 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 Irving Fluor
124 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 Irving Builders FirstSource
125 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 Irving Vistra
126 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 Irving Caterpillar
127 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 Irving McKesson
128 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston Waste Management
129 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston Plains GP
130 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston NRG Energy
131 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston EOG Resources
132 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston Targa Resources
133 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 Irving Commercial Metals
134 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 Irving Celanese
135 75243 33 -97 63,907 POINT (-96.73633 32.91232) Texas 2432800 2,680,800,000,000 Dallas Texas Instruments
136 75074 33 -97 53,146 POINT (-96.67304 33.03298) Texas 2432800 2,680,800,000,000 Plano Yum China s
137 75201 33 -97 18,078 POINT (-96.79953 32.78826) Texas 2432800 2,680,800,000,000 Dallas CBRE
138 75201 33 -97 18,078 POINT (-96.79953 32.78826) Texas 2432800 2,680,800,000,000 Dallas Jacobs Solutions
139 75202 33 -97 2,744 POINT (-96.8037 32.77843) Texas 2432800 2,680,800,000,000 Dallas AT&T
140 75219 33 -97 25,001 POINT (-96.81315 32.81087) Texas 2432800 2,680,800,000,000 Dallas HF Sinclair
141 75225 33 -97 22,383 POINT (-96.79109 32.86511) Texas 2432800 2,680,800,000,000 Dallas Energy Transfer
142 75235 33 -97 19,067 POINT (-96.84798 32.83219) Texas 2432800 2,680,800,000,000 Dallas Southwest Airlines
143 75240 33 -97 24,718 POINT (-96.78924 32.93194) Texas 2432800 2,680,800,000,000 Dallas AECOM
144 76155 33 -97 6,301 POINT (-97.04911 32.82404) Texas 2432800 2,680,800,000,000 Fort Worth American Airlines
145 76011 33 -97 22,297 POINT (-97.08223 32.7543) Texas 2432800 2,680,800,000,000 Arlington D.R. Horton
146 75254 33 -97 24,737 POINT (-96.80127 32.94571) Texas 2432800 2,680,800,000,000 Dallas Tenet Healthcare
147 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston Kinder Morgan
148 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston Cheniere Energy
149 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston Enterprise Products Partners
150 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston CenterPoint Energy
151 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston KBR
152 78682 30 -98 0 POINT (-97.7273 30.4076) Texas 2432800 2,680,800,000,000 Round Rock Dell Technologies
153 78288 29 -98 0 POINT (-98.4935 29.4239) Texas 2432800 2,680,800,000,000 San Antonio USAA
154 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 Houston Chevron
155 79701 32 -102 27,678 POINT (-102.08105 31.99239) Texas 2432800 2,680,800,000,000 Midland Diamondback Energy
156 78741 30 -98 45,274 POINT (-97.71389 30.23007) Texas 2432800 2,680,800,000,000 Austin Oracle
157 78725 30 -98 10,810 POINT (-97.60859 30.23554) Texas 2432800 2,680,800,000,000 Austin Tesla
158 78249 30 -99 61,772 POINT (-98.614 29.56752) Texas 2432800 2,680,800,000,000 San Antonio Valero Energy
159 78130 30 -98 95,787 POINT (-98.06877 29.69224) Texas 2432800 2,680,800,000,000 New Braunfels Rush Enterprises
160 77389 30 -96 44,545 POINT (-95.50752 30.11509) Texas 2432800 2,680,800,000,000 Spring Hewlett Packard
161 77389 30 -96 44,545 POINT (-95.50752 30.11509) Texas 2432800 2,680,800,000,000 Spring Exxon Mobil
162 77079 30 -96 35,540 POINT (-95.6037 29.77632) Texas 2432800 2,680,800,000,000 Houston Baker Hughes
163 77079 30 -96 35,540 POINT (-95.6037 29.77632) Texas 2432800 2,680,800,000,000 Houston ConocoPhillips
164 77077 30 -96 63,421 POINT (-95.64189 29.75375) Texas 2432800 2,680,800,000,000 Houston Sysco
165 77056 30 -95 23,314 POINT (-95.46806 29.74849) Texas 2432800 2,680,800,000,000 Houston Westlake
166 77046 30 -95 1,873 POINT (-95.43301 29.73438) Texas 2432800 2,680,800,000,000 Houston Occidental Petroleum
167 77042 30 -96 40,725 POINT (-95.56015 29.74125) Texas 2432800 2,680,800,000,000 Houston NOV
168 77042 30 -96 40,725 POINT (-95.56015 29.74125) Texas 2432800 2,680,800,000,000 Houston APA
169 77042 30 -96 40,725 POINT (-95.56015 29.74125) Texas 2432800 2,680,800,000,000 Houston Phillips 66
170 77032 30 -95 13,536 POINT (-95.34004 29.96523) Texas 2432800 2,680,800,000,000 Houston Halliburton
171 77024 30 -96 37,647 POINT (-95.50869 29.77073) Texas 2432800 2,680,800,000,000 Houston Par Pacific
172 77024 30 -96 37,647 POINT (-95.50869 29.77073) Texas 2432800 2,680,800,000,000 Houston 1 Automotive
173 77019 30 -95 23,662 POINT (-95.41212 29.75318) Texas 2432800 2,680,800,000,000 Houston Corebridge Financial
174 77008 30 -95 40,155 POINT (-95.41766 29.79856) Texas 2432800 2,680,800,000,000 Houston Quanta Services
175 76262 33 -97 43,589 POINT (-97.22101 33.01137) Texas 2432800 2,680,800,000,000 Westlake Charles Schwab
176 72762 36 -94 47,402 POINT (-94.22794 36.18747) Arkansas 2283200 764,300,000,000 Springdale Tyson Foods
177 72745 36 -94 14,521 POINT (-94.10046 36.2477) Arkansas 2283200 764,300,000,000 Lowell J.B. Hunt Transport Services
178 72712 36 -94 38,072 POINT (-94.22196 36.39837) Arkansas 2283200 764,300,000,000 Bentonville Walmart
179 71730 33 -93 29,187 POINT (-92.63458 33.20303) Arkansas 2283200 764,300,000,000 El Dorado Murphy USA
180 61710 41 -89 79,633 POINT (-88.9894 40.516) Illinois 1655400 1,040,200,000,000 Bloomington State Farm
181 60607 42 -88 30,197 POINT (-87.65175 41.87467) Illinois 1655400 1,040,200,000,000 Chicago Mondelez
182 60064 42 -88 15,047 POINT (-87.86122 42.3237) Illinois 1655400 1,040,200,000,000 Abbott Park Abbott Laboratories
183 60523 42 -88 10,012 POINT (-87.95406 41.83713) Illinois 1655400 1,040,200,000,000 Oak Brook Ace Hardware
184 60015 42 -88 27,720 POINT (-87.87486 42.17239) Illinois 1655400 1,040,200,000,000 Deerfield Walgreens
185 60015 42 -88 27,720 POINT (-87.87486 42.17239) Illinois 1655400 1,040,200,000,000 Riverwoods Discover Financial
186 60015 42 -88 27,720 POINT (-87.87486 42.17239) Illinois 1655400 1,040,200,000,000 Deerfield Baxter International
187 60018 42 -88 29,302 POINT (-87.89846 41.99629) Illinois 1655400 1,040,200,000,000 Rosemont US Foods
188 60025 42 -88 40,877 POINT (-87.81204 42.07466) Illinois 1655400 1,040,200,000,000 Glenview Illinois Tool Works
189 60045 42 -88 20,957 POINT (-87.87006 42.23807) Illinois 1655400 1,040,200,000,000 Lake Forest W.W. Grainger
190 60045 42 -88 20,957 POINT (-87.87006 42.23807) Illinois 1655400 1,040,200,000,000 Lake Forest Packaging Corp. of America
191 60061 42 -88 27,883 POINT (-87.96046 42.2334) Illinois 1655400 1,040,200,000,000 Vernon Hills CDW
192 60062 42 -88 41,667 POINT (-87.84235 42.12663) Illinois 1655400 1,040,200,000,000 Northbrook Allstate
193 60064 42 -88 15,047 POINT (-87.86122 42.3237) Illinois 1655400 1,040,200,000,000 North Chicago AbbVie
194 60154 42 -88 16,524 POINT (-87.88986 41.84923) Illinois 1655400 1,040,200,000,000 Westchester Ingredion
195 60440 42 -88 52,074 POINT (-88.07572 41.70125) Illinois 1655400 1,040,200,000,000 Bolingbrook Ulta Beauty
196 60008 42 -88 22,949 POINT (-88.0229 42.0739) Illinois 1655400 1,040,200,000,000 Rolling Meadows Arthur J. Gallagher
197 60515 42 -88 29,045 POINT (-88.0247 41.80991) Illinois 1655400 1,040,200,000,000 Downers Grove Dover
198 60601 42 -88 16,292 POINT (-87.62197 41.88527) Illinois 1655400 1,040,200,000,000 Chicago Archer Daniels Midland
199 60606 42 -88 3,527 POINT (-87.63724 41.88178) Illinois 1655400 1,040,200,000,000 Chicago Molson Coors Beverage
200 60661 42 -88 11,516 POINT (-87.64409 41.88291) Illinois 1655400 1,040,200,000,000 Chicago Motorola Solutions
201 60661 42 -88 11,516 POINT (-87.64409 41.88291) Illinois 1655400 1,040,200,000,000 Chicago GE HealthCare Technologies
202 60654 42 -88 24,303 POINT (-87.63673 41.89209) Illinois 1655400 1,040,200,000,000 Chicago Conagra Brands
203 60654 42 -88 24,303 POINT (-87.63673 41.89209) Illinois 1655400 1,040,200,000,000 Chicago Kellanova
204 60607 42 -88 30,197 POINT (-87.65175 41.87467) Illinois 1655400 1,040,200,000,000 Chicago McDonald's
205 60601 42 -88 16,292 POINT (-87.62197 41.88527) Illinois 1655400 1,040,200,000,000 Chicago Kraft Heinz
206 61265 41 -90 43,851 POINT (-90.48895 41.48195) Illinois 1655400 1,040,200,000,000 Moline Deere
207 60606 42 -88 3,527 POINT (-87.63724 41.88178) Illinois 1655400 1,040,200,000,000 Chicago United Airlines
208 60603 42 -88 1,126 POINT (-87.6274 41.88018) Illinois 1655400 1,040,200,000,000 Chicago Northern Trust
209 60603 42 -88 1,126 POINT (-87.6274 41.88018) Illinois 1655400 1,040,200,000,000 Chicago Exelon
210 60601 42 -88 16,292 POINT (-87.62197 41.88527) Illinois 1655400 1,040,200,000,000 Chicago Old Republic International
211 60601 42 -88 16,292 POINT (-87.62197 41.88527) Illinois 1655400 1,040,200,000,000 Chicago Jones Lang LaSalle
212 20190 39 -77 22,092 POINT (-77.33806 38.95968) Virginia 1461200 738,400,000,000 Reston General Dynamics
213 20170 39 -77 43,372 POINT (-77.38042 38.98075) Virginia 1461200 738,400,000,000 Herndon QXO Building Products
214 20147 39 -77 67,007 POINT (-77.47958 39.04151) Virginia 1461200 738,400,000,000 Ashburn DXC Technology
215 20190 39 -77 22,092 POINT (-77.33806 38.95968) Virginia 1461200 738,400,000,000 Reston Leidos s
216 23238 38 -78 25,893 POINT (-77.64138 37.59595) Virginia 1461200 738,400,000,000 Richmond Performance Food
217 23607 37 -76 23,028 POINT (-76.42235 36.98753) Virginia 1461200 738,400,000,000 Newport News Huntington Ingalls Industries
218 23606 37 -76 29,899 POINT (-76.49557 37.07847) Virginia 1461200 738,400,000,000 Newport News Ferguson
219 23320 37 -76 59,626 POINT (-76.21807 36.75208) Virginia 1461200 738,400,000,000 Chesapeake Dollar Tree
220 20190 39 -77 22,092 POINT (-77.33806 38.95968) Virginia 1461200 738,400,000,000 Reston CACI International
221 23238 38 -78 25,893 POINT (-77.64138 37.59595) Virginia 1461200 738,400,000,000 Richmond CarMax
222 20190 39 -77 22,092 POINT (-77.33806 38.95968) Virginia 1461200 738,400,000,000 Reston NVR
223 23230 38 -77 8,304 POINT (-77.49153 37.587) Virginia 1461200 738,400,000,000 Richmond Altria
224 20190 39 -77 22,092 POINT (-77.33806 38.95968) Virginia 1461200 738,400,000,000 Reston Science Applications International
225 22203 39 -77 25,921 POINT (-77.1164 38.87377) Virginia 1461200 738,400,000,000 Arlington AES
226 22042 39 -77 34,631 POINT (-77.19406 38.86463) Virginia 1461200 738,400,000,000 Falls Church Northrop Grumman
227 23060 38 -78 36,111 POINT (-77.53427 37.65981) Virginia 1461200 738,400,000,000 Glen Allen Markel
228 23060 38 -78 36,111 POINT (-77.53427 37.65981) Virginia 1461200 738,400,000,000 Glen Allen Owens & Minor
229 23219 38 -77 3,856 POINT (-77.43484 37.54076) Virginia 1461200 738,400,000,000 Richmond Dominion Energy
230 23227 38 -77 25,574 POINT (-77.44234 37.61486) Virginia 1461200 738,400,000,000 Richmond ARKO
231 22209 39 -77 13,725 POINT (-77.07309 38.89413) Virginia 1461200 738,400,000,000 Arlington RTX
232 22202 39 -77 27,352 POINT (-77.05175 38.8569) Virginia 1461200 738,400,000,000 Arlington Boeing
233 22102 39 -77 28,577 POINT (-77.22901 38.95199) Virginia 1461200 738,400,000,000 McLean Hilton
234 22102 39 -77 28,577 POINT (-77.22901 38.95199) Virginia 1461200 738,400,000,000 McLean Capital One
235 22102 39 -77 28,577 POINT (-77.22901 38.95199) Virginia 1461200 738,400,000,000 McLean Freddie Mac
236 22102 39 -77 28,577 POINT (-77.22901 38.95199) Virginia 1461200 738,400,000,000 McLean Booz Allen Hamilton
237 30326 34 -84 8,497 POINT (-84.36342 33.84957) Georgia 1327300 548,300,000,000 Atlanta Global Payments
238 30354 34 -84 15,487 POINT (-84.38609 33.66058) Georgia 1327300 548,300,000,000 Atlanta Delta Airlines
239 30339 34 -84 34,872 POINT (-84.46483 33.86786) Georgia 1327300 548,300,000,000 Atlanta Assurant
240 30339 34 -84 34,872 POINT (-84.46483 33.86786) Georgia 1327300 548,300,000,000 Atlanta Genuine Parts
241 30339 34 -84 34,872 POINT (-84.46483 33.86786) Georgia 1327300 548,300,000,000 Atlanta Home Depot
242 30328 34 -84 38,821 POINT (-84.38617 33.93194) Georgia 1327300 548,300,000,000 Atlanta Newell Brands
243 30328 34 -84 38,821 POINT (-84.38617 33.93194) Georgia 1327300 548,300,000,000 Atlanta Graphic Packaging
244 30328 34 -84 38,821 POINT (-84.38617 33.93194) Georgia 1327300 548,300,000,000 Atlanta Intercontinental Exchange
245 30328 34 -84 38,821 POINT (-84.38617 33.93194) Georgia 1327300 548,300,000,000 Atlanta UPS
246 30308 34 -84 23,329 POINT (-84.37773 33.77094) Georgia 1327300 548,300,000,000 Atlanta Norfolk Southern
247 30326 34 -84 8,497 POINT (-84.36342 33.84957) Georgia 1327300 548,300,000,000 Atlanta Pulte
248 30313 34 -84 10,845 POINT (-84.39761 33.76369) Georgia 1327300 548,300,000,000 Atlanta Coca-Cola
249 30308 34 -84 23,329 POINT (-84.37773 33.77094) Georgia 1327300 548,300,000,000 Atlanta Southern
250 30097 34 -84 45,543 POINT (-84.14702 34.0271) Georgia 1327300 548,300,000,000 Duluth Asbury Automotive
251 30096 34 -84 71,141 POINT (-84.14791 33.97691) Georgia 1327300 548,300,000,000 Duluth AGCO
252 31999 32 -85 3,469 POINT (-84.98772 32.46078) Georgia 1327300 548,300,000,000 Columbus Aflac
253 30701 34 -85 43,078 POINT (-84.95385 34.49535) Georgia 1327300 548,300,000,000 Calhoun Mohawk Industries
254 55144 45 -93 11,636 POINT (-93.04758 44.92912) Minnesota 1269900 802,600,000,000 St. Paul 3M
255 55144 45 -93 11,636 POINT (-93.04758 44.92912) Minnesota 1269900 802,600,000,000 Maplewood Solventum
256 55474 45 -93 28,071 POINT (-93.27 44.98) Minnesota 1269900 802,600,000,000 Minneapolis Ameriprise Financial
257 55347 45 -93 30,467 POINT (-93.46638 44.82931) Minnesota 1269900 802,600,000,000 Eden Prairie C.H. Robinson Worldwide
258 55077 45 -93 14,585 POINT (-93.07574 44.81989) Minnesota 1269900 802,600,000,000 Inver Grove Heights CHS
259 55402 45 -93 760 POINT (-93.27119 44.97608) Minnesota 1269900 802,600,000,000 Minneapolis U.S. Bancorp
260 55987 44 -92 33,911 POINT (-91.63143 43.98469) Minnesota 1269900 802,600,000,000 Winona Fastenal
261 55912 44 -93 29,438 POINT (-92.99148 43.6827) Minnesota 1269900 802,600,000,000 Austin Hormel Foods
262 55426 45 -93 25,451 POINT (-93.38139 44.95635) Minnesota 1269900 802,600,000,000 Minneapolis General Mills
263 55423 45 -93 36,779 POINT (-93.28144 44.87663) Minnesota 1269900 802,600,000,000 Richfield Best Buy
264 55415 45 -93 6,474 POINT (-93.2578 44.97463) Minnesota 1269900 802,600,000,000 Minneapolis Thrivent Financial for Lutherans
265 55403 45 -93 17,354 POINT (-93.28588 44.97023) Minnesota 1269900 802,600,000,000 Minneapolis Target
266 55101 45 -93 7,937 POINT (-93.08739 44.95111) Minnesota 1269900 802,600,000,000 St. Paul Securian Financial
267 55102 45 -93 19,565 POINT (-93.12149 44.93216) Minnesota 1269900 802,600,000,000 St. Paul Ecolab
268 55126 45 -93 27,484 POINT (-93.13581 45.08614) Minnesota 1269900 802,600,000,000 Arden Hills Land O'Lakes
269 55344 45 -93 14,180 POINT (-93.43037 44.86452) Minnesota 1269900 802,600,000,000 Eden Prairie UnitedHealth
270 55401 45 -93 11,526 POINT (-93.26984 44.98526) Minnesota 1269900 802,600,000,000 Minneapolis Xcel Energy
271 44115 41 -82 10,389 POINT (-81.66999 41.49211) Ohio 1255100 1,035,800,000,000 Cleveland Sherwin-Williams
272 43287 40 -83 905,748 POINT (-83.0011 39.9619) Ohio 1255100 1,035,800,000,000 Columbus Huntington Bancshares
273 43659 42 -84 0 POINT (-83.5554 41.6639) Ohio 1255100 1,035,800,000,000 Toledo Owens Corning
274 45840 41 -84 54,342 POINT (-83.64943 41.02626) Ohio 1255100 1,035,800,000,000 Findlay Marathon Petroleum
275 45262 39 -84 0 POINT (-84.4569 39.1616) Ohio 1255100 1,035,800,000,000 Cincinnati Cintas
276 45263 39 -84 0 POINT (-84.4569 39.1616) Ohio 1255100 1,035,800,000,000 Cincinnati Fifth Third Bancorp
277 44316 41 -81 0 POINT (-81.47083 41.07854) Ohio 1255100 1,035,800,000,000 Akron Goodyear Tire & Rubber
278 45215 39 -84 30,806 POINT (-84.46221 39.23536) Ohio 1255100 1,035,800,000,000 Evendale General Electric
279 44114 42 -82 7,472 POINT (-81.67625 41.5137) Ohio 1255100 1,035,800,000,000 Cleveland KeyCorp
280 45202 39 -85 17,022 POINT (-84.50243 39.10885) Ohio 1255100 1,035,800,000,000 Cincinnati American Financial
281 44114 42 -82 7,472 POINT (-81.67625 41.5137) Ohio 1255100 1,035,800,000,000 Cleveland Cleveland-Cliffs
282 44115 41 -82 10,389 POINT (-81.66999 41.49211) Ohio 1255100 1,035,800,000,000 Cleveland TransDigm
283 43615 42 -84 40,813 POINT (-83.67255 41.65045) Ohio 1255100 1,035,800,000,000 Toledo Welltower
284 43537 42 -84 29,639 POINT (-83.68542 41.57433) Ohio 1255100 1,035,800,000,000 Maumee Dana
285 43537 42 -84 29,639 POINT (-83.68542 41.57433) Ohio 1255100 1,035,800,000,000 Maumee Andersons
286 43215 40 -83 16,999 POINT (-83.01262 39.96633) Ohio 1255100 1,035,800,000,000 Columbus American Electric Power
287 43215 40 -83 16,999 POINT (-83.01262 39.96633) Ohio 1255100 1,035,800,000,000 Columbus Nationwide
288 43082 40 -83 33,799 POINT (-82.88437 40.15537) Ohio 1255100 1,035,800,000,000 Westerville Vertiv s
289 43017 40 -83 41,422 POINT (-83.13314 40.1189) Ohio 1255100 1,035,800,000,000 Dublin Cardinal Health
290 44124 41 -81 40,046 POINT (-81.46774 41.49999) Ohio 1255100 1,035,800,000,000 Cleveland Parker-Hannifin
291 44143 42 -81 24,337 POINT (-81.47513 41.55358) Ohio 1255100 1,035,800,000,000 Mayfield Village Progressive
292 44308 41 -82 1,261 POINT (-81.51751 41.0818) Ohio 1255100 1,035,800,000,000 Akron FirstEnergy
293 44667 41 -82 13,688 POINT (-81.76495 40.83386) Ohio 1255100 1,035,800,000,000 Orrville J.M. Smucker
294 45014 39 -85 45,652 POINT (-84.5521 39.32822) Ohio 1255100 1,035,800,000,000 Fairfield Cincinnati Financial
295 45202 39 -85 17,022 POINT (-84.50243 39.10885) Ohio 1255100 1,035,800,000,000 Cincinnati Kroger
296 45202 39 -85 17,022 POINT (-84.50243 39.10885) Ohio 1255100 1,035,800,000,000 Cincinnati Procter & Gamble
297 45202 39 -85 17,022 POINT (-84.50243 39.10885) Ohio 1255100 1,035,800,000,000 Cincinnati Western & Southern Financial
298 44060 42 -81 60,257 POINT (-81.32806 41.67742) Ohio 1255100 1,035,800,000,000 Mentor Avery Dennison
In [145]:
musmaxempst10 = gdfstsusmaxempst10.explore(column='Employees', name='The Biggest Employer State in US visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactusmaxempst10.explore(m=musmaxempst10, column='Employees', name='The Biggest Employer State in US visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(musmaxempst10)
musmaxempst10
Out[145]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [146]:
# The Most Efficient City in US
dfusmaxeffct = df.groupby(['State','City'], as_index=False).sum('Employees')
dfusmaxeffct.insert(4,'Efficiency',1)
dfusmaxeffct['Efficiency'] = dfusmaxeffct['Revenue (rounded)'] / dfusmaxeffct['Employees']
dfusmaxeffct = dfusmaxeffct.sort_values('Efficiency', ascending=False).reset_index(drop=True)
dfusmaxeffct10 = dfusmaxeffct.head(10)
dfusmaxeffct
Out[146]:
State City Employees Revenue (rounded) Efficiency
0 California El Segundo 500 9,700,000,000 19,400,000
1 Ohio Findlay 18300 140,400,000,000 7,672,131
2 Oklahoma Oklahoma City 2300 15,900,000,000 6,913,043
3 Pennsylvania Conshohocken 44000 294,000,000,000 6,681,818
4 Texas Midland 2000 11,100,000,000 5,550,000
5 Missouri Chesterfield 4100 22,100,000,000 5,390,244
6 Ohio Dublin 48400 226,800,000,000 4,685,950
7 Minnesota Inver Grove Heights 10700 39,300,000,000 3,672,897
8 Texas San Antonio 47900 172,600,000,000 3,603,340
9 Connecticut Bloomfield 72400 247,100,000,000 3,412,983
10 Florida Miami 25300 85,200,000,000 3,367,589
11 Texas Spring 121900 379,700,000,000 3,114,848
12 Oklahoma Tulsa 11000 32,200,000,000 2,927,273
13 California Los Gatos 14000 39,000,000,000 2,785,714
14 Massachusetts Springfield 21900 55,000,000,000 2,511,416
15 Texas Arlington 14800 36,800,000,000 2,486,486
16 California Cupertino 164000 391,000,000,000 2,384,146
17 California Long Beach 18000 40,600,000,000 2,255,556
18 California Menlo Park 74100 164,500,000,000 2,219,973
19 Pennsylvania Fort Washington 4900 10,800,000,000 2,204,082
20 Michigan Lansing 7300 15,800,000,000 2,164,384
21 Ohio Fairfield 5600 11,300,000,000 2,017,857
22 District of Columbia Washington 93200 185,200,000,000 1,987,124
23 Pennsylvania Erie 6700 13,200,000,000 1,970,149
24 Wisconsin Madison 11100 21,300,000,000 1,918,919
25 Pennsylvania Radnor 9800 18,400,000,000 1,877,551
26 California Irvine 26100 48,000,000,000 1,839,080
27 Illinois Bloomington 67400 123,000,000,000 1,824,926
28 Minnesota Arden Hills 9000 16,200,000,000 1,800,000
29 Rhode Island Johnston 5800 10,400,000,000 1,793,103
30 California Mountain View 207500 366,300,000,000 1,765,301
31 California Fremont 43200 73,400,000,000 1,699,074
32 Maryland Baltimore 14200 23,600,000,000 1,661,972
33 California Foster City 17600 28,800,000,000 1,636,364
34 Texas Houston 557600 906,500,000,000 1,625,717
35 Texas Irving 287000 462,000,000,000 1,609,756
36 New Jersey Newark 50900 80,700,000,000 1,585,462
37 California Woodland Hills 9900 15,500,000,000 1,565,657
38 Arkansas El Dorado 11600 17,900,000,000 1,543,103
39 Ohio Columbus 58700 90,300,000,000 1,538,330
40 Georgia Columbus 12700 18,900,000,000 1,488,189
41 Florida Juno Beach 16800 24,800,000,000 1,476,190
42 Rhode Island Woonsocket 259500 372,800,000,000 1,436,609
43 New Jersey Parsippany 38200 54,200,000,000 1,418,848
44 New Jersey Princeton 34100 48,300,000,000 1,416,422
45 Illinois Vernon Hills 15100 21,000,000,000 1,390,728
46 Connecticut Hartford 19100 26,500,000,000 1,387,435
47 Indiana Indianapolis 172700 238,900,000,000 1,383,324
48 Indiana Fort Wayne 13000 17,500,000,000 1,346,154
49 Colorado Centennial 21500 27,900,000,000 1,297,674
50 Missouri St. Louis 160700 207,500,000,000 1,291,226
51 Virginia Richmond 99300 127,000,000,000 1,278,953
52 Illinois Rosemont 30000 37,900,000,000 1,263,333
53 California Rosemead 14000 17,600,000,000 1,257,143
54 California Corona 6000 7,500,000,000 1,250,000
55 California Oakland 39800 48,500,000,000 1,218,593
56 Oregon Medford 30200 36,600,000,000 1,211,921
57 Virginia Herndon 8100 9,800,000,000 1,209,877
58 Michigan Midland 36000 43,000,000,000 1,194,444
59 California Thousand Oaks 28000 33,400,000,000 1,192,857
60 Michigan Detroit 182200 216,300,000,000 1,187,157
61 Tennessee Chattanooga 10900 12,900,000,000 1,183,486
62 Illinois Northbrook 55200 64,100,000,000 1,161,232
63 Arizona Scottsdale 19000 22,000,000,000 1,157,895
64 Ohio Mayfield Village 66300 75,400,000,000 1,137,255
65 Illinois Riverwoods 21000 23,600,000,000 1,123,810
66 California Palo Alto 95000 106,000,000,000 1,115,789
67 Michigan Dearborn 171000 185,000,000,000 1,081,871
68 New York Victor 9300 10,000,000,000 1,075,269
69 Washington Redmond 228000 245,100,000,000 1,075,000
70 Florida Fort Lauderdale 25100 26,800,000,000 1,067,729
71 Michigan Bloomfield Hills 28900 30,500,000,000 1,055,363
72 Illinois North Chicago 55000 56,300,000,000 1,023,636
73 California Santa Clara 250200 255,600,000,000 1,021,583
74 Kentucky Louisville 134400 136,600,000,000 1,016,369
75 Minnesota Eden Prairie 413800 418,000,000,000 1,010,150
76 Texas New Braunfels 7900 7,800,000,000 987,342
77 Louisiana New Orleans 12300 11,900,000,000 967,480
78 New York Tarrytown 15100 14,200,000,000 940,397
79 Illinois Moline 55500 51,700,000,000 931,532
80 Nebraska Omaha 463100 427,000,000,000 922,047
81 Massachusetts Boston 115500 106,400,000,000 921,212
82 Ohio Orrville 9000 8,200,000,000 911,111
83 Wisconsin Milwaukee 106900 96,700,000,000 904,584
84 Washington Bellevue 49000 44,300,000,000 904,082
85 Michigan Jackson 8300 7,500,000,000 903,614
86 California Beverly Hills 34200 30,700,000,000 897,661
87 New York New York 2028200 1,820,500,000,000 897,594
88 Texas Round Rock 108000 95,600,000,000 885,185
89 New Jersey Rahway 74000 64,200,000,000 867,568
90 California San Diego 74800 64,600,000,000 863,636
91 California San Mateo 10200 8,500,000,000 833,333
92 Iowa Des Moines 19700 16,100,000,000 817,259
93 Texas Westlake 32100 26,000,000,000 809,969
94 Colorado Englewood 32700 25,800,000,000 788,991
95 Arizona Tempe 17400 13,700,000,000 787,356
96 North Carolina Charlotte 422700 331,300,000,000 783,771
97 Washington Issaquah 333000 254,500,000,000 764,264
98 Illinois Oak Brook 12500 9,500,000,000 760,000
99 Colorado Westminster 16000 12,100,000,000 756,250
100 Georgia Duluth 39000 28,900,000,000 741,026
101 Ohio Toledo 25700 19,000,000,000 739,300
102 Ohio Evendale 53000 38,700,000,000 730,189
103 Rhode Island Providence 79600 57,100,000,000 717,337
104 Virginia McLean 275900 197,900,000,000 717,289
105 Pennsylvania Allentown 29100 20,600,000,000 707,904
106 New Jersey Summit 22000 15,500,000,000 704,545
107 Tennessee Kingsport 14000 9,400,000,000 671,429
108 Tennessee Brentwood 41000 27,400,000,000 668,293
109 New Jersey Camden 14400 9,600,000,000 666,667
110 Florida Sunny Isles Beach 15000 10,000,000,000 666,667
111 Florida Plantation 18000 11,900,000,000 661,111
112 Illinois Westchester 11200 7,400,000,000 660,714
113 Kansas Merriam 14000 9,100,000,000 650,000
114 California Milpitas 15100 9,800,000,000 649,007
115 Oregon Beaverton 79400 51,400,000,000 647,355
116 New Jersey New Brunswick 138100 88,800,000,000 643,012
117 Illinois Lake Forest 40400 25,600,000,000 633,663
118 Michigan Byron Center 15000 9,500,000,000 633,333
119 Florida Jacksonville 114900 71,700,000,000 624,021
120 Florida Tampa 36800 22,900,000,000 622,283
121 Texas Dallas 590100 366,500,000,000 621,081
122 California San Jose 248200 153,000,000,000 616,438
123 New York Buffalo 22100 13,500,000,000 610,860
124 Virginia Glen Allen 45200 27,300,000,000 603,982
125 Arizona Phoenix 121000 73,000,000,000 603,306
126 California San Francisco 492000 296,000,000,000 601,626
127 California Redwood City 27300 16,300,000,000 597,070
128 New York Long Island City 30700 18,300,000,000 596,091
129 California Manhattan Beach 15100 9,000,000,000 596,026
130 Minnesota Austin 20000 11,900,000,000 595,000
131 Connecticut Norwalk 64600 38,300,000,000 592,879
132 Connecticut Stamford 225500 132,500,000,000 587,583
133 Pennsylvania Hershey 19300 11,200,000,000 580,311
134 Wisconsin Oshkosh 18500 10,700,000,000 578,378
135 Pennsylvania Pittsburgh 209800 119,200,000,000 568,160
136 Illinois Deerfield 290500 162,800,000,000 560,413
137 California Sunnyvale 15600 8,400,000,000 538,462
138 Alabama Birmingham 31600 16,800,000,000 531,646
139 Texas Austin 284700 150,700,000,000 529,329
140 Massachusetts Cambridge 84400 44,600,000,000 528,436
141 Louisiana Monroe 25000 13,100,000,000 524,000
142 Massachusetts Burlington 29400 15,400,000,000 523,810
143 Virginia Newport News 79000 41,100,000,000 520,253
144 Florida Palm Beach Gardens 48000 24,800,000,000 516,667
145 Delaware Wilmington 24000 12,400,000,000 516,667
146 Ohio Maumee 41900 21,600,000,000 515,513
147 Illinois Chicago 724600 368,100,000,000 508,004
148 New York Melville 25000 12,700,000,000 508,000
149 Indiana Columbus 69600 34,100,000,000 489,943
150 Minnesota Richfield 85000 41,500,000,000 488,235
151 Massachusetts Waltham 128800 60,100,000,000 466,615
152 Ohio Cincinnati 593500 276,100,000,000 465,206
153 Pennsylvania Canonsburg 32000 14,700,000,000 459,375
154 Florida Melbourne 47000 21,300,000,000 453,191
155 Indiana Warsaw 17000 7,700,000,000 452,941
156 Iowa Ankeny 33100 14,900,000,000 450,151
157 Indiana Elkhart 22300 10,000,000,000 448,430
158 California Burbank 205000 91,400,000,000 445,854
159 Arizona Chandler 36600 16,300,000,000 445,355
160 Virginia Arlington 367100 159,500,000,000 434,487
161 Michigan Livonia 18000 7,800,000,000 433,333
162 Massachusetts Marlborough 86000 37,200,000,000 432,558
163 Michigan Portage 53000 22,600,000,000 426,415
164 Idaho Boise 244600 104,300,000,000 426,410
165 Virginia Falls Church 97000 41,000,000,000 422,680
166 Minnesota St. Paul 115100 48,500,000,000 421,373
167 Ohio Cleveland 188400 79,300,000,000 420,913
168 Colorado Denver 123800 51,200,000,000 413,570
169 Virginia Reston 220000 90,300,000,000 410,455
170 California Pleasanton 20500 8,400,000,000 409,756
171 Texas Fort Worth 133300 54,200,000,000 406,602
172 Ohio Akron 80300 31,900,000,000 397,260
173 Georgia Atlanta 1233700 489,700,000,000 396,936
174 North Carolina Raleigh 65300 25,900,000,000 396,631
175 Massachusetts Wilmington 24000 9,400,000,000 391,667
176 North Carolina Mooresville 215500 83,700,000,000 388,399
177 Arkansas Springdale 138000 53,300,000,000 386,232
178 Michigan Benton Harbor 44000 16,600,000,000 377,273
179 Minnesota Maplewood 22000 8,300,000,000 377,273
180 Minnesota Minneapolis 573300 211,400,000,000 368,742
181 Illinois Abbott Park 114000 42,000,000,000 368,421
182 Illinois Glenview 44000 15,900,000,000 361,364
183 Arkansas Lowell 33600 12,100,000,000 360,119
184 Pennsylvania Coraopolis 37400 13,400,000,000 358,289
185 Minnesota Winona 21000 7,500,000,000 357,143
186 Washington Seattle 2101600 744,900,000,000 354,444
187 Illinois Downers Grove 24000 8,400,000,000 350,000
188 Maryland Bethesda 276000 96,100,000,000 348,188
189 Florida Estero 26000 9,000,000,000 346,154
190 New York Purchase 354300 120,100,000,000 338,978
191 Arkansas Bentonville 2100000 681,000,000,000 324,286
192 Connecticut New Britain 48500 15,400,000,000 317,526
193 Pennsylvania Philadelphia 448700 141,100,000,000 314,464
194 Tennessee Antioch 47000 14,400,000,000 306,383
195 Florida Coral Gables 82700 24,900,000,000 301,088
196 New Jersey Roseland 64000 19,200,000,000 300,000
197 Missouri Des Peres 55000 16,300,000,000 296,364
198 Indiana Evansville 42000 12,300,000,000 292,857
199 Illinois Bolingbrook 39000 11,300,000,000 289,744
200 Florida St. Petersburg 157000 43,800,000,000 278,981
201 New Jersey Franklin Lakes 74000 20,200,000,000 272,973
202 Washington Sumner 39000 10,600,000,000 271,795
203 Wisconsin Menomonee Falls 60000 16,200,000,000 270,000
204 Nevada Las Vegas 109100 28,500,000,000 261,228
205 Tennessee Nashville 271000 70,600,000,000 260,517
206 Ohio Westerville 31000 8,000,000,000 258,065
207 Georgia Calhoun 41900 10,800,000,000 257,757
208 Ohio Mentor 35000 8,800,000,000 251,429
209 Michigan Auburn Hills 100600 24,500,000,000 243,539
210 Tennessee Franklin 52500 12,600,000,000 240,000
211 Connecticut Greenwich 179600 42,800,000,000 238,307
212 Florida Lakeland 255000 60,200,000,000 236,078
213 New York Corning 56300 13,100,000,000 232,682
214 Nevada Reno 50000 11,300,000,000 226,000
215 New Jersey Burlington 47300 10,600,000,000 224,101
216 Tennessee Memphis 559900 124,800,000,000 222,897
217 New York Armonk 284500 62,800,000,000 220,738
218 Virginia Chesapeake 139600 30,800,000,000 220,630
219 Tennessee Goodlettsville 194200 40,600,000,000 209,063
220 Illinois Rolling Meadows 56000 11,600,000,000 207,143
221 California Newport Beach 134800 27,100,000,000 201,039
222 North Carolina Burlington 65400 13,000,000,000 198,777
223 Connecticut Farmington 72000 14,300,000,000 198,611
224 California Dublin 107000 21,100,000,000 197,196
225 New Jersey Secaucus 50500 9,900,000,000 196,040
226 Missouri Springfield 85600 16,700,000,000 195,093
227 Pennsylvania King of Prussia 87500 15,800,000,000 180,571
228 North Carolina Durham 88000 15,400,000,000 175,000
229 Massachusetts Framingham 364000 56,400,000,000 154,945
230 Michigan Southfield 173700 23,300,000,000 134,139
231 Connecticut Wallingford 125000 15,200,000,000 121,600
232 Virginia Ashburn 130000 13,700,000,000 105,385
233 Florida Orlando 191100 11,400,000,000 59,655
234 New Jersey Teaneck 336800 19,700,000,000 58,492
235 Texas Plano 245500 11,300,000,000 46,029
236 California Newark 450000 9,600,000,000 21,333
In [147]:
dfusmaxeffct10 = dfusmaxeffct10.merge(df[['State','City','Company','Zip Code']], how = 'inner', on = ['State','City'])

gdfstsusmaxeffct10 = gdfsts.merge(dfusmaxeffct10, how = 'inner', on = ['State'])
gdfusactusmaxeffct10 = gdfusact.merge(dfusmaxeffct10, how = 'inner', on = ['Zip Code']).sort_values('Efficiency', ascending=False).reset_index(drop=True)
gdfusactusmaxeffct10
Out[147]:
Zip Code Latitude Longitude Population geometry State City Employees Revenue (rounded) Efficiency Company
0 90245 34 -118 16,863 POINT (-118.40161 33.91709) California El Segundo 500 9,700,000,000 19,400,000 A-Mark Precious Metals
1 45840 41 -84 54,342 POINT (-83.64943 41.02626) Ohio Findlay 18300 140,400,000,000 7,672,131 Marathon Petroleum
2 73102 35 -98 3,590 POINT (-97.5191 35.47065) Oklahoma Oklahoma City 2300 15,900,000,000 6,913,043 Devon Energy
3 19428 40 -75 20,225 POINT (-75.30317 40.08011) Pennsylvania Conshohocken 44000 294,000,000,000 6,681,818 Cencora
4 79701 32 -102 27,678 POINT (-102.08105 31.99239) Texas Midland 2000 11,100,000,000 5,550,000 Diamondback Energy
5 63017 39 -91 43,074 POINT (-90.53722 38.65143) Missouri Chesterfield 4100 22,100,000,000 5,390,244 Reinsurance of America
6 43017 40 -83 41,422 POINT (-83.13314 40.1189) Ohio Dublin 48400 226,800,000,000 4,685,950 Cardinal Health
7 55077 45 -93 14,585 POINT (-93.07574 44.81989) Minnesota Inver Grove Heights 10700 39,300,000,000 3,672,897 CHS
8 78249 30 -99 61,772 POINT (-98.614 29.56752) Texas San Antonio 47900 172,600,000,000 3,603,340 Valero Energy
9 78288 29 -98 0 POINT (-98.4935 29.4239) Texas San Antonio 47900 172,600,000,000 3,603,340 USAA
10 06002 42 -73 21,547 POINT (-72.73714 41.84286) Connecticut Bloomfield 72400 247,100,000,000 3,412,983 Cigna
In [148]:
musmaxeffct10 = gdfstsusmaxeffct10.explore(column='Efficiency', name='The Most Efficient City in US visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactusmaxeffct10.explore(m=musmaxeffct10, column='Efficiency', name='The Most Efficient City in US visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(musmaxeffct10)
musmaxeffct10
Out[148]:
Make this Notebook Trusted to load map: File -> Trust Notebook
In [ ]:
 
In [149]:
# The Most Efficient State in US
dfusmaxeffst = df.groupby(['State'], as_index=False).sum('Employees')
dfusmaxeffst.insert(3,'Efficiency',1)
dfusmaxeffst['Efficiency'] = dfusmaxeffst['Revenue (rounded)'] / dfusmaxeffst['Employees']
dfusmaxeffst = dfusmaxeffst.sort_values('Efficiency', ascending=False).reset_index(drop=True)
dfusmaxeffst10 = dfusmaxeffst.head(10)
dfusmaxeffst
Out[149]:
State Employees Revenue (rounded) Efficiency
0 Oklahoma 13300 48,100,000,000 3,616,541
1 District of Columbia 93200 185,200,000,000 1,987,124
2 Rhode Island 344900 440,300,000,000 1,276,602
3 Texas 2432800 2,680,800,000,000 1,101,940
4 Kentucky 134400 136,600,000,000 1,016,369
5 Indiana 336600 320,500,000,000 952,169
6 Nebraska 463100 427,000,000,000 922,047
7 Missouri 305400 262,600,000,000 859,856
8 California 2857700 2,399,300,000,000 839,591
9 Ohio 1255100 1,035,800,000,000 825,273
10 Oregon 109600 88,000,000,000 802,920
11 New York 2825500 2,085,200,000,000 737,993
12 Wisconsin 196500 144,900,000,000 737,405
13 Pennsylvania 929200 672,400,000,000 723,633
14 Michigan 838000 602,400,000,000 718,854
15 Louisiana 37300 25,000,000,000 670,241
16 Connecticut 806700 532,100,000,000 659,601
17 Kansas 14000 9,100,000,000 650,000
18 Arizona 194000 125,000,000,000 644,330
19 Minnesota 1269900 802,600,000,000 632,018
20 Illinois 1655400 1,040,200,000,000 628,368
21 Colorado 194000 117,000,000,000 603,093
22 Iowa 52800 31,000,000,000 587,121
23 North Carolina 856900 469,300,000,000 547,672
24 Alabama 31600 16,800,000,000 531,646
25 Delaware 24000 12,400,000,000 516,667
26 Virginia 1461200 738,400,000,000 505,338
27 Washington 2750600 1,299,400,000,000 472,406
28 New Jersey 944300 440,900,000,000 466,907
29 Massachusetts 854000 384,500,000,000 450,234
30 Idaho 244600 104,300,000,000 426,410
31 Florida 1058700 448,700,000,000 423,822
32 Georgia 1327300 548,300,000,000 413,094
33 Maryland 290200 119,700,000,000 412,474
34 Arkansas 2283200 764,300,000,000 334,749
35 Tennessee 1190500 312,700,000,000 262,663
36 Nevada 159100 39,800,000,000 250,157
In [150]:
dfusmaxeffst10 = dfusmaxeffst10.merge(df[['State','City','Company','Zip Code']], how = 'inner', on = ['State'])

gdfstsusmaxeffst10 = gdfsts.merge(dfusmaxeffst10, how = 'inner', on = ['State'])
gdfusactusmaxeffst10 = gdfusact.merge(dfusmaxeffst10, how = 'inner', on = ['Zip Code']).sort_values('Efficiency', ascending=False).reset_index(drop=True)
gdfusactusmaxeffst10
Out[150]:
Zip Code Latitude Longitude Population geometry State Employees Revenue (rounded) Efficiency City Company
0 74172 36 -96 0 POINT (-95.9905 36.1544) Oklahoma 13300 48,100,000,000 3,616,541 Tulsa Williams
1 73102 35 -98 3,590 POINT (-97.5191 35.47065) Oklahoma 13300 48,100,000,000 3,616,541 Oklahoma City Devon Energy
2 74103 36 -96 2,419 POINT (-95.9957 36.15617) Oklahoma 13300 48,100,000,000 3,616,541 Tulsa Oneok
3 20037 39 -77 12,441 POINT (-77.0535 38.89213) District of Columbia 93200 185,200,000,000 1,987,124 Washington Danaher
4 20003 39 -77 36,194 POINT (-76.99033 38.88193) District of Columbia 93200 185,200,000,000 1,987,124 Washington Xylem
5 20005 39 -77 12,960 POINT (-77.0316 38.90443) District of Columbia 93200 185,200,000,000 1,987,124 Washington Fannie Mae
6 02903 42 -71 12,309 POINT (-71.41003 41.81902) Rhode Island 344900 440,300,000,000 1,276,602 Providence Textron
7 02895 42 -71 43,081 POINT (-71.49923 42.00103) Rhode Island 344900 440,300,000,000 1,276,602 Woonsocket CVS Health
8 02919 42 -72 29,473 POINT (-71.52002 41.82733) Rhode Island 344900 440,300,000,000 1,276,602 Johnston FM
9 02908 42 -71 39,661 POINT (-71.43926 41.83877) Rhode Island 344900 440,300,000,000 1,276,602 Providence United Natural Foods
10 02903 42 -71 12,309 POINT (-71.41003 41.81902) Rhode Island 344900 440,300,000,000 1,276,602 Providence Citizens Financial
11 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 1,101,940 Houston Targa Resources
12 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 1,101,940 Houston Waste Management
13 76011 33 -97 22,297 POINT (-97.08223 32.7543) Texas 2432800 2,680,800,000,000 1,101,940 Arlington D.R. Horton
14 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 1,101,940 Houston EOG Resources
15 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 1,101,940 Houston NRG Energy
16 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 1,101,940 Houston Plains GP
17 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 1,101,940 Houston Enterprise Products Partners
18 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 1,101,940 Houston Chevron
19 76262 33 -97 43,589 POINT (-97.22101 33.01137) Texas 2432800 2,680,800,000,000 1,101,940 Westlake Charles Schwab
20 76155 33 -97 6,301 POINT (-97.04911 32.82404) Texas 2432800 2,680,800,000,000 1,101,940 Fort Worth American Airlines
21 75225 33 -97 22,383 POINT (-96.79109 32.86511) Texas 2432800 2,680,800,000,000 1,101,940 Dallas Energy Transfer
22 75254 33 -97 24,737 POINT (-96.80127 32.94571) Texas 2432800 2,680,800,000,000 1,101,940 Dallas Tenet Healthcare
23 75243 33 -97 63,907 POINT (-96.73633 32.91232) Texas 2432800 2,680,800,000,000 1,101,940 Dallas Texas Instruments
24 75240 33 -97 24,718 POINT (-96.78924 32.93194) Texas 2432800 2,680,800,000,000 1,101,940 Dallas AECOM
25 75235 33 -97 19,067 POINT (-96.84798 32.83219) Texas 2432800 2,680,800,000,000 1,101,940 Dallas Southwest Airlines
26 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 1,101,940 Houston Kinder Morgan
27 75219 33 -97 25,001 POINT (-96.81315 32.81087) Texas 2432800 2,680,800,000,000 1,101,940 Dallas HF Sinclair
28 75202 33 -97 2,744 POINT (-96.8037 32.77843) Texas 2432800 2,680,800,000,000 1,101,940 Dallas AT&T
29 75201 33 -97 18,078 POINT (-96.79953 32.78826) Texas 2432800 2,680,800,000,000 1,101,940 Dallas Jacobs Solutions
30 75201 33 -97 18,078 POINT (-96.79953 32.78826) Texas 2432800 2,680,800,000,000 1,101,940 Dallas CBRE
31 75074 33 -97 53,146 POINT (-96.67304 33.03298) Texas 2432800 2,680,800,000,000 1,101,940 Plano Yum China s
32 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 1,101,940 Houston Cheniere Energy
33 77019 30 -95 23,662 POINT (-95.41212 29.75318) Texas 2432800 2,680,800,000,000 1,101,940 Houston Corebridge Financial
34 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 1,101,940 Houston CenterPoint Energy
35 77002 30 -95 19,616 POINT (-95.36538 29.75635) Texas 2432800 2,680,800,000,000 1,101,940 Houston KBR
36 78682 30 -98 0 POINT (-97.7273 30.4076) Texas 2432800 2,680,800,000,000 1,101,940 Round Rock Dell Technologies
37 78288 29 -98 0 POINT (-98.4935 29.4239) Texas 2432800 2,680,800,000,000 1,101,940 San Antonio USAA
38 79701 32 -102 27,678 POINT (-102.08105 31.99239) Texas 2432800 2,680,800,000,000 1,101,940 Midland Diamondback Energy
39 78741 30 -98 45,274 POINT (-97.71389 30.23007) Texas 2432800 2,680,800,000,000 1,101,940 Austin Oracle
40 78725 30 -98 10,810 POINT (-97.60859 30.23554) Texas 2432800 2,680,800,000,000 1,101,940 Austin Tesla
41 78249 30 -99 61,772 POINT (-98.614 29.56752) Texas 2432800 2,680,800,000,000 1,101,940 San Antonio Valero Energy
42 78130 30 -98 95,787 POINT (-98.06877 29.69224) Texas 2432800 2,680,800,000,000 1,101,940 New Braunfels Rush Enterprises
43 77389 30 -96 44,545 POINT (-95.50752 30.11509) Texas 2432800 2,680,800,000,000 1,101,940 Spring Hewlett Packard
44 77389 30 -96 44,545 POINT (-95.50752 30.11509) Texas 2432800 2,680,800,000,000 1,101,940 Spring Exxon Mobil
45 77079 30 -96 35,540 POINT (-95.6037 29.77632) Texas 2432800 2,680,800,000,000 1,101,940 Houston Baker Hughes
46 77079 30 -96 35,540 POINT (-95.6037 29.77632) Texas 2432800 2,680,800,000,000 1,101,940 Houston ConocoPhillips
47 77077 30 -96 63,421 POINT (-95.64189 29.75375) Texas 2432800 2,680,800,000,000 1,101,940 Houston Sysco
48 77056 30 -95 23,314 POINT (-95.46806 29.74849) Texas 2432800 2,680,800,000,000 1,101,940 Houston Westlake
49 77046 30 -95 1,873 POINT (-95.43301 29.73438) Texas 2432800 2,680,800,000,000 1,101,940 Houston Occidental Petroleum
50 77042 30 -96 40,725 POINT (-95.56015 29.74125) Texas 2432800 2,680,800,000,000 1,101,940 Houston NOV
51 77042 30 -96 40,725 POINT (-95.56015 29.74125) Texas 2432800 2,680,800,000,000 1,101,940 Houston APA
52 77042 30 -96 40,725 POINT (-95.56015 29.74125) Texas 2432800 2,680,800,000,000 1,101,940 Houston Phillips 66
53 77032 30 -95 13,536 POINT (-95.34004 29.96523) Texas 2432800 2,680,800,000,000 1,101,940 Houston Halliburton
54 77024 30 -96 37,647 POINT (-95.50869 29.77073) Texas 2432800 2,680,800,000,000 1,101,940 Houston Par Pacific
55 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 1,101,940 Irving Celanese
56 77008 30 -95 40,155 POINT (-95.41766 29.79856) Texas 2432800 2,680,800,000,000 1,101,940 Houston Quanta Services
57 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 1,101,940 Irving Commercial Metals
58 77024 30 -96 37,647 POINT (-95.50869 29.77073) Texas 2432800 2,680,800,000,000 1,101,940 Houston 1 Automotive
59 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 1,101,940 Irving Fluor
60 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 1,101,940 Irving Vistra
61 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 1,101,940 Irving Caterpillar
62 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 1,101,940 Irving McKesson
63 75038 33 -97 33,097 POINT (-96.97946 32.87231) Texas 2432800 2,680,800,000,000 1,101,940 Irving Kimberly-Clark
64 75039 33 -97 22,450 POINT (-96.94042 32.88592) Texas 2432800 2,680,800,000,000 1,101,940 Irving Builders FirstSource
65 40213 38 -86 15,805 POINT (-85.71571 38.177) Kentucky 134400 136,600,000,000 1,016,369 Louisville Yum Brands
66 40222 38 -86 21,634 POINT (-85.61173 38.26436) Kentucky 134400 136,600,000,000 1,016,369 Louisville BrightSpring Health Services
67 40202 38 -86 7,109 POINT (-85.75205 38.25288) Kentucky 134400 136,600,000,000 1,016,369 Louisville Humana
68 46285 40 -86 0 POINT (-86.1582 39.7683) Indiana 336600 320,500,000,000 952,169 Indianapolis Eli Lilly
69 47710 38 -88 18,802 POINT (-87.57618 38.02518) Indiana 336600 320,500,000,000 952,169 Evansville Berry Global
70 47201 39 -86 48,602 POINT (-85.99432 39.15074) Indiana 336600 320,500,000,000 952,169 Columbus Cummins
71 46804 41 -85 29,177 POINT (-85.23913 41.05421) Indiana 336600 320,500,000,000 952,169 Fort Wayne Steel Dynamics
72 46580 41 -86 21,812 POINT (-85.87212 41.20884) Indiana 336600 320,500,000,000 952,169 Warsaw Zimmer Biomet s
73 46514 42 -86 41,480 POINT (-85.97547 41.72328) Indiana 336600 320,500,000,000 952,169 Elkhart THOR Industries
74 46268 40 -86 25,623 POINT (-86.23253 39.89769) Indiana 336600 320,500,000,000 952,169 Indianapolis Corteva
75 46204 40 -86 11,022 POINT (-86.15703 39.77134) Indiana 336600 320,500,000,000 952,169 Indianapolis Elevance Health
76 68175 41 -96 0 POINT (-95.96584 41.26502) Nebraska 463100 427,000,000,000 922,047 Omaha Mutual of Omaha Insurance
77 68131 41 -96 13,928 POINT (-95.96479 41.26435) Nebraska 463100 427,000,000,000 922,047 Omaha Berkshire Hathaway
78 68179 41 -96 0 POINT (-95.9352 41.2597) Nebraska 463100 427,000,000,000 922,047 Omaha Union Pacific
79 68102 41 -96 9,311 POINT (-95.93224 41.26231) Nebraska 463100 427,000,000,000 922,047 Omaha Peter Kiewit Sons'
80 65802 37 -93 46,005 POINT (-93.35167 37.21048) Missouri 305400 262,600,000,000 859,856 Springfield O'Reilly Automotive
81 63144 39 -90 9,580 POINT (-90.3482 38.61943) Missouri 305400 262,600,000,000 859,856 St. Louis Post s
82 63146 39 -90 30,917 POINT (-90.47634 38.70135) Missouri 305400 262,600,000,000 859,856 St. Louis Core & Main
83 63105 39 -90 18,860 POINT (-90.32812 38.64427) Missouri 305400 262,600,000,000 859,856 St. Louis Centene
84 63105 39 -90 18,860 POINT (-90.32812 38.64427) Missouri 305400 262,600,000,000 859,856 St. Louis Graybar Electric
85 63131 39 -90 17,993 POINT (-90.44365 38.6172) Missouri 305400 262,600,000,000 859,856 Des Peres Edward Jones
86 63017 39 -91 43,074 POINT (-90.53722 38.65143) Missouri 305400 262,600,000,000 859,856 Chesterfield Reinsurance of America
87 63136 39 -90 41,314 POINT (-90.25979 38.74418) Missouri 305400 262,600,000,000 859,856 St. Louis Emerson Electric
88 94588 38 -122 34,423 POINT (-121.88178 37.73801) California 2857700 2,399,300,000,000 839,591 Pleasanton Workday
89 94304 37 -122 4,731 POINT (-122.16699 37.39744) California 2857700 2,399,300,000,000 839,591 Palo Alto HP
90 94560 38 -122 47,145 POINT (-122.02523 37.50771) California 2857700 2,399,300,000,000 839,591 Newark Concentrix
91 94538 38 -122 67,704 POINT (-121.96361 37.50653) California 2857700 2,399,300,000,000 839,591 Fremont Lam Research
92 94538 38 -122 67,704 POINT (-121.96361 37.50653) California 2857700 2,399,300,000,000 839,591 Fremont TD Synnex
93 94404 38 -122 35,950 POINT (-122.26905 37.5562) California 2857700 2,399,300,000,000 839,591 Foster City Gilead Sciences
94 94403 38 -122 43,459 POINT (-122.30454 37.53844) California 2857700 2,399,300,000,000 839,591 San Mateo Franklin Resources
95 94304 37 -122 4,731 POINT (-122.16699 37.39744) California 2857700 2,399,300,000,000 839,591 Palo Alto Broadcom
96 94111 38 -122 4,553 POINT (-122.3998 37.79847) California 2857700 2,399,300,000,000 839,591 San Francisco Prologis
97 94158 38 -122 11,206 POINT (-122.39153 37.77116) California 2857700 2,399,300,000,000 839,591 San Francisco Uber
98 94109 38 -122 54,397 POINT (-122.42138 37.79334) California 2857700 2,399,300,000,000 839,591 San Francisco Williams-Sonoma
99 94107 38 -122 30,190 POINT (-122.39508 37.76473) California 2857700 2,399,300,000,000 839,591 San Francisco DoorDash
100 94105 38 -122 14,890 POINT (-122.39707 37.79239) California 2857700 2,399,300,000,000 839,591 San Francisco Gap
101 94105 38 -122 14,890 POINT (-122.39707 37.79239) California 2857700 2,399,300,000,000 839,591 San Francisco Visa
102 94105 38 -122 14,890 POINT (-122.39707 37.79239) California 2857700 2,399,300,000,000 839,591 San Francisco Salesforce
103 94104 38 -122 478 POINT (-122.40211 37.79144) California 2857700 2,399,300,000,000 839,591 San Francisco Wells Fargo
104 94568 38 -122 70,542 POINT (-121.90113 37.71596) California 2857700 2,399,300,000,000 839,591 Dublin Ross Stores
105 95125 37 -122 53,934 POINT (-121.89408 37.29554) California 2857700 2,399,300,000,000 839,591 San Jose Ebay
106 94612 38 -122 17,663 POINT (-122.2662 37.80789) California 2857700 2,399,300,000,000 839,591 Oakland PG&E
107 95054 37 -122 25,196 POINT (-121.96483 37.39308) California 2857700 2,399,300,000,000 839,591 Santa Clara Palo Alto Networks
108 95134 37 -122 30,255 POINT (-121.94528 37.43003) California 2857700 2,399,300,000,000 839,591 San Jose Sanmina
109 95134 37 -122 30,255 POINT (-121.94528 37.43003) California 2857700 2,399,300,000,000 839,591 San Jose Cisco Systems
110 95131 37 -122 30,745 POINT (-121.89793 37.38729) California 2857700 2,399,300,000,000 839,591 San Jose Super Micro Computer
111 95131 37 -122 30,745 POINT (-121.89793 37.38729) California 2857700 2,399,300,000,000 839,591 San Jose PayPal
112 94086 37 -122 48,956 POINT (-122.02316 37.37164) California 2857700 2,399,300,000,000 839,591 Sunnyvale Intuitive Surgical
113 95119 37 -122 10,449 POINT (-121.79077 37.22756) California 2857700 2,399,300,000,000 839,591 San Jose Western Digital
114 95110 37 -122 19,444 POINT (-121.9097 37.34656) California 2857700 2,399,300,000,000 839,591 San Jose Adobe
115 95054 37 -122 25,196 POINT (-121.96483 37.39308) California 2857700 2,399,300,000,000 839,591 Santa Clara ServiceNow
116 94612 38 -122 17,663 POINT (-122.2662 37.80789) California 2857700 2,399,300,000,000 839,591 Oakland Block
117 95054 37 -122 25,196 POINT (-121.96483 37.39308) California 2857700 2,399,300,000,000 839,591 Santa Clara Advanced Micro Devices
118 95054 37 -122 25,196 POINT (-121.96483 37.39308) California 2857700 2,399,300,000,000 839,591 Santa Clara Applied Materials
119 95054 37 -122 25,196 POINT (-121.96483 37.39308) California 2857700 2,399,300,000,000 839,591 Santa Clara Intel
120 95051 37 -122 61,345 POINT (-121.98444 37.3483) California 2857700 2,399,300,000,000 839,591 Santa Clara Nvidia
121 95035 37 -122 78,479 POINT (-121.87632 37.44319) California 2857700 2,399,300,000,000 839,591 Milpitas KLA
122 95032 37 -122 27,682 POINT (-121.92359 37.20859) California 2857700 2,399,300,000,000 839,591 Los Gatos Netflix
123 95014 37 -122 61,109 POINT (-122.07981 37.30827) California 2857700 2,399,300,000,000 839,591 Cupertino Apple
124 94103 38 -122 33,524 POINT (-122.41136 37.77299) California 2857700 2,399,300,000,000 839,591 San Francisco Airbnb
125 92612 34 -118 33,706 POINT (-117.82457 33.65984) California 2857700 2,399,300,000,000 839,591 Irvine Ingram Micro
126 94065 38 -122 11,620 POINT (-122.24683 37.53504) California 2857700 2,399,300,000,000 839,591 Redwood City Electronic Arts
127 91770 34 -118 58,893 POINT (-118.08361 34.06395) California 2857700 2,399,300,000,000 839,591 Rosemead Edison International
128 94065 38 -122 11,620 POINT (-122.24683 37.53504) California 2857700 2,399,300,000,000 839,591 Redwood City Equinix
129 90210 34 -118 19,652 POINT (-118.41505 34.10251) California 2857700 2,399,300,000,000 839,591 Beverly Hills Live Nation Entertainment
130 90210 34 -118 19,652 POINT (-118.41505 34.10251) California 2857700 2,399,300,000,000 839,591 Beverly Hills Endeavor
131 90245 34 -118 16,863 POINT (-118.40161 33.91709) California 2857700 2,399,300,000,000 839,591 El Segundo A-Mark Precious Metals
132 90266 34 -118 34,584 POINT (-118.39705 33.88968) California 2857700 2,399,300,000,000 839,591 Manhattan Beach Skechers U.S.A.
133 90802 34 -118 39,859 POINT (-118.21143 33.75035) California 2857700 2,399,300,000,000 839,591 Long Beach Molina Healthcare
134 91320 34 -119 43,628 POINT (-118.94795 34.17339) California 2857700 2,399,300,000,000 839,591 Thousand Oaks Amgen
135 91367 34 -119 45,427 POINT (-118.61518 34.17708) California 2857700 2,399,300,000,000 839,591 Woodland Hills Farmers Insurance Exchange
136 91521 34 -118 11,049 POINT (-118.3252 34.1569) California 2857700 2,399,300,000,000 839,591 Burbank Walt Disney
137 92101 33 -117 48,163 POINT (-117.18589 32.7162) California 2857700 2,399,300,000,000 839,591 San Diego Sempra
138 92121 33 -117 4,157 POINT (-117.20231 32.8973) California 2857700 2,399,300,000,000 839,591 San Diego LPL Financial s
139 92660 34 -118 34,788 POINT (-117.87504 33.63375) California 2857700 2,399,300,000,000 839,591 Newport Beach Pacific Life
140 92660 34 -118 34,788 POINT (-117.87504 33.63375) California 2857700 2,399,300,000,000 839,591 Newport Beach Chipotle Mexican Grill
141 92879 34 -118 48,756 POINT (-117.5357 33.87979) California 2857700 2,399,300,000,000 839,591 Corona Monster Beverage
142 94025 37 -122 40,230 POINT (-122.1829 37.45087) California 2857700 2,399,300,000,000 839,591 Menlo Park Meta
143 94043 37 -122 32,042 POINT (-122.06892 37.41188) California 2857700 2,399,300,000,000 839,591 Mountain View Alphabet
144 92121 33 -117 4,157 POINT (-117.20231 32.8973) California 2857700 2,399,300,000,000 839,591 San Diego Qualcomm
145 94043 37 -122 32,042 POINT (-122.06892 37.41188) California 2857700 2,399,300,000,000 839,591 Mountain View Intuit
146 45263 39 -84 0 POINT (-84.4569 39.1616) Ohio 1255100 1,035,800,000,000 825,273 Cincinnati Fifth Third Bancorp
147 43287 40 -83 905,748 POINT (-83.0011 39.9619) Ohio 1255100 1,035,800,000,000 825,273 Columbus Huntington Bancshares
148 43659 42 -84 0 POINT (-83.5554 41.6639) Ohio 1255100 1,035,800,000,000 825,273 Toledo Owens Corning
149 44316 41 -81 0 POINT (-81.47083 41.07854) Ohio 1255100 1,035,800,000,000 825,273 Akron Goodyear Tire & Rubber
150 45262 39 -84 0 POINT (-84.4569 39.1616) Ohio 1255100 1,035,800,000,000 825,273 Cincinnati Cintas
151 45202 39 -85 17,022 POINT (-84.50243 39.10885) Ohio 1255100 1,035,800,000,000 825,273 Cincinnati Western & Southern Financial
152 45202 39 -85 17,022 POINT (-84.50243 39.10885) Ohio 1255100 1,035,800,000,000 825,273 Cincinnati Kroger
153 45202 39 -85 17,022 POINT (-84.50243 39.10885) Ohio 1255100 1,035,800,000,000 825,273 Cincinnati Procter & Gamble
154 44667 41 -82 13,688 POINT (-81.76495 40.83386) Ohio 1255100 1,035,800,000,000 825,273 Orrville J.M. Smucker
155 45202 39 -85 17,022 POINT (-84.50243 39.10885) Ohio 1255100 1,035,800,000,000 825,273 Cincinnati American Financial
156 45215 39 -84 30,806 POINT (-84.46221 39.23536) Ohio 1255100 1,035,800,000,000 825,273 Evendale General Electric
157 45840 41 -84 54,342 POINT (-83.64943 41.02626) Ohio 1255100 1,035,800,000,000 825,273 Findlay Marathon Petroleum
158 45014 39 -85 45,652 POINT (-84.5521 39.32822) Ohio 1255100 1,035,800,000,000 825,273 Fairfield Cincinnati Financial
159 44115 41 -82 10,389 POINT (-81.66999 41.49211) Ohio 1255100 1,035,800,000,000 825,273 Cleveland Sherwin-Williams
160 44308 41 -82 1,261 POINT (-81.51751 41.0818) Ohio 1255100 1,035,800,000,000 825,273 Akron FirstEnergy
161 44143 42 -81 24,337 POINT (-81.47513 41.55358) Ohio 1255100 1,035,800,000,000 825,273 Mayfield Village Progressive
162 44124 41 -81 40,046 POINT (-81.46774 41.49999) Ohio 1255100 1,035,800,000,000 825,273 Cleveland Parker-Hannifin
163 44115 41 -82 10,389 POINT (-81.66999 41.49211) Ohio 1255100 1,035,800,000,000 825,273 Cleveland TransDigm
164 44114 42 -82 7,472 POINT (-81.67625 41.5137) Ohio 1255100 1,035,800,000,000 825,273 Cleveland KeyCorp
165 44114 42 -82 7,472 POINT (-81.67625 41.5137) Ohio 1255100 1,035,800,000,000 825,273 Cleveland Cleveland-Cliffs
166 44060 42 -81 60,257 POINT (-81.32806 41.67742) Ohio 1255100 1,035,800,000,000 825,273 Mentor Avery Dennison
167 43615 42 -84 40,813 POINT (-83.67255 41.65045) Ohio 1255100 1,035,800,000,000 825,273 Toledo Welltower
168 43537 42 -84 29,639 POINT (-83.68542 41.57433) Ohio 1255100 1,035,800,000,000 825,273 Maumee Andersons
169 43215 40 -83 16,999 POINT (-83.01262 39.96633) Ohio 1255100 1,035,800,000,000 825,273 Columbus American Electric Power
170 43215 40 -83 16,999 POINT (-83.01262 39.96633) Ohio 1255100 1,035,800,000,000 825,273 Columbus Nationwide
171 43082 40 -83 33,799 POINT (-82.88437 40.15537) Ohio 1255100 1,035,800,000,000 825,273 Westerville Vertiv s
172 43017 40 -83 41,422 POINT (-83.13314 40.1189) Ohio 1255100 1,035,800,000,000 825,273 Dublin Cardinal Health
173 43537 42 -84 29,639 POINT (-83.68542 41.57433) Ohio 1255100 1,035,800,000,000 825,273 Maumee Dana
In [151]:
musmaxeffst10 = gdfstsusmaxeffst10.explore(column='Efficiency', name='The Most Efficient State in US visualized by State', cmap='coolwarm', edgecolor='black', marker_kwds={'radius': 5})
gdfusactusmaxeffst10.explore(m=musmaxeffst10, column='Efficiency', name='The Most Efficient State in US visualized by City', cmap='RdYlGn', edgecolor='black', marker_kwds={'radius': 5})
folium.LayerControl().add_to(musmaxeffst10)
musmaxeffst10
Out[151]:
Make this Notebook Trusted to load map: File -> Trust Notebook
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